{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorflow version: 2.0.0\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "print('Tensorflow version: {}'.format(tf.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import  matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pathlib\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_root = pathlib.Path('F:\\hu_jingrui-zhenjiakankankan-master\\zhenjiakankankan\\Shoes_Check\\AJ_Picture')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F:\\hu_jingrui-zhenjiakankankan-master\\zhenjiakankankan\\Shoes_Check\\AJ_Picture\\AJ1\n",
      "F:\\hu_jingrui-zhenjiakankankan-master\\zhenjiakankankan\\Shoes_Check\\AJ_Picture\\AJ11\n",
      "F:\\hu_jingrui-zhenjiakankankan-master\\zhenjiakankankan\\Shoes_Check\\AJ_Picture\\AJ12\n",
      "F:\\hu_jingrui-zhenjiakankankan-master\\zhenjiakankankan\\Shoes_Check\\AJ_Picture\\AJ4\n"
     ]
    }
   ],
   "source": [
    "for item in data_root.iterdir():\n",
    "    print(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 提取出所有路径的所有对象\n",
    "all_image_path = list(data_root.glob('*/*'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[WindowsPath('F:/hu_jingrui-zhenjiakankankan-master/zhenjiakankankan/Shoes_Check/AJ_Picture/AJ4/F7.JPG'),\n",
       " WindowsPath('F:/hu_jingrui-zhenjiakankankan-master/zhenjiakankankan/Shoes_Check/AJ_Picture/AJ4/F8.JPG'),\n",
       " WindowsPath('F:/hu_jingrui-zhenjiakankankan-master/zhenjiakankankan/Shoes_Check/AJ_Picture/AJ4/F9.JPG')]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_image_path[-3:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#列表推导式转化地址格式\n",
    "all_image_path = [str(path) for path in all_image_path]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 随机打乱顺序\n",
    "random.shuffle(all_image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['F:\\\\hu_jingrui-zhenjiakankankan-master\\\\zhenjiakankankan\\\\Shoes_Check\\\\AJ_Picture\\\\AJ12\\\\T19.JPG',\n",
       " 'F:\\\\hu_jingrui-zhenjiakankankan-master\\\\zhenjiakankankan\\\\Shoes_Check\\\\AJ_Picture\\\\AJ11\\\\E4.JPG']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_image_path[10: 12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_count = len(all_image_path)\n",
    "image_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取文件夹名生成标签\n",
    "label_names = sorted(item.name for item in data_root.glob('*/'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AJ1', 'AJ11', 'AJ12', 'AJ4']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_to_index = dict((name, index) for index, name in enumerate(label_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'AJ1': 0, 'AJ11': 1, 'AJ12': 2, 'AJ4': 3}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_to_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 通过上一级目录将图片与标签一一对应\n",
    "all_image_label = [label_to_index[pathlib.Path(p).parent.name] for p in all_image_path]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3, 3, 1, 1, 1]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_image_label[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 有显示图片等一系列功能\n",
    "import IPython.display as display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "index_to_label = dict((v, k) for k,v in label_to_index.items())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 'AJ1', 1: 'AJ11', 2: 'AJ12', 3: 'AJ4'}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_to_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AJ4\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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KUcuTtDG83G05xq5zjlzeYH6Usmcdt7iTq45hl8IvqByNJiuwzsILkxzdTTSNaPIeZ9FxMb2TdhZMkXEmTEuDRTdzzry80qu0ZxoFgtznN/K/Qf8AcrlQY/ByBveNa/MNXV4vM+vkV5rEdm+LYfEOhLo5XxgF2R2Zo6C1xRBxKMWcNK5odTq1DiFaPZtZBIA6KTLTcxIN/wAda81e4OpMjX1qTVaVsvHwcVlie4y5gN6cKIP9Fzo+0DqDM7gADWWtDzryVo9fheKcU4WWuwuLliH1FgdbfcFer4X24bIAzi0IZ1mhGg8y3+i+Y4bjpDju0O+lt2GnzPP0XLj43G91SMJbz6t/xeie0fb45GSxtkie2SNwtr2GwVlzXyjhHaGbAF0nDpy2xmfG+ix+u5H+yvbcM7YYPF5YuIN+SnI+om43HyPL3WYPQIo1wewPY4PYdnNNg+6qgJaKIKoiIKiIgiIiAiLi8Q4jheF4Q4jGvLWbNaBbnuq6AQclAbutQOY2XybjvbHF46dr5ZnQ4Z5IZCySmWORI1HrzXn4u1XFsNMx2DxYwuR15o9ddhZ5j1RY+8ovN9i+1sfajh8jZGiPG4WhKBtK07SNHLXQhekRE9UREBOSIgIiIIiqiDSiKoJSoRVQEVRAROaoVBERQFVFVQVURBUREFRRVARPROaAqoiCoiICqUiAiIgIiICIlIKnJFUERVRARVKQEREDdVFPVAREQVERAREQEREBERAREQEREBEQoI5zGNc+R2VjQXOd0AFkr4f2l4tJxvjk2Oc4N759RtJ0ZGNGj/fVfRu33HBw7g/7PgeBiMaw5+rIhv7k6elr5BM7NM0uaS0AX5orGCF88zYAS2TvDmAF02tSsuK4+MkQw6MZbWtewChyroFyYyMLw44hrh3kjfDI40coP+wvPYyb5mfwNIc7cXf6qo1xt+ZnDHOIZeuq7nC4fhUWGd8w175hoC11WuujhDY9KzN3bWq2sc1jRKWNc06bfzUHc8QwUmfBF8jMHg8WC0TuZ4Glo3cB50P1pcnhfFsT2cdjH4WYvw+ZkRbKARI8glzSNiBv7hcPB9o58FgZcC/DYLiGFnF9zjIM+Rw2cNdCuvmxT8TIxjmQwxsGVscDQ1jOpA6nmd0V6CHEzYtxxbWNijALIy92VhP4jXQDpzUjxWHZhgcUInOB8TySXydAByH/AHXTRl8jmtEl0AMpFDTal2cMk0Mj3ywxYgtvXMPCSNXDz6Ko5zZMOyRsmKYGOB0jLiBlrcjWztpsufg5cHiGx4iec3TnxBrqLQBTTtpt9l0kWMGGgccThu8fIK7yRlkDy5DktsbnzRESREA7ARlznV0y6epOgRXPnn4HLHNieO4fvDCzLFHFZzSu0bf667DouRwjsHwF8MsnaOGXB2c4j77K5ra28uq4ETG43iEceCa/9n4WMyYrFSODTOXfhYT6Vz2XYNmjbC0vfK2BzyWtzmR0nmb2AP3UHIf8PeybOFnFTP4lh+/s4f8Ae3lZye4Ec9TXReX4l2Lmwb8P+zsZnOJce7hlPjA/DfQka15hc/iHaDEvxYlbJbIXWSXV4q0FLpxxV7sUyeZ7pHhxeRel72qjgv8An+GOIxMD2hmmdpsDy91z8L2iogZsumxNrmu4tGeHRQSwhz5JXYiUk2W2Ka32GvqU4hgOGYmOAGNnzD4Y3EMFUSNnHrsUo53DO1cuDcHYTFugvXKx1NJ/y7L1+A+IsTi2LiUQLiP7SHQnzLdvsvnEvAsK1kbsNinsztc52t5HA7enQrWeDYsRSO+c1houDmUWg7FWj7Zhe1HBMY6o+IRxHpMMmvTXmu1bUkYkjIew6h7DYI9Qvz4cBxKKISNkhma4keF3Mcjf8VycDx3i/BZC6F88NEEmIksU6H3pF854R8U+8pnEcOycULki8DvOxsvX4HtXwPiAaIeIMje78E4yEe+yQduqo2n/AEEO/wApB/gqdN1BEREBfP8At9js2J7q3NZCe6Dh1ItxHWhQX0EauAJoXuvkXxFxb3TQjFwlrpe9LY2nLXjyg/Yfqi48rgMBL2i49h+FYZwLsXMGtmym44x9Ry/4RZte4+KHZuDAcF4djeFYd3yuCi+TmcwAU3+7e88zdj3W34T8McXcQ4vNkkyAYOCXL4nDQu9KFNXvuKcNh4xwjF8NxIBjxURjNi8p5OryNFC9vinw84weG9rsL3jiI8R/w8pvWnbfY0vutEGnbg0V+bYTLhcaAW5TDIY2+GtQf9F+j4ZvmcNDOP72Nr/uAgyRXkoiCIiAih38kvRBVCqog0qqKoFKqBVBUURQVERBUUVQVFFVQREQFVFVBVE9VUBEVQRVRVAREVFREQEREBFUQEREBVRVAREQNgsA4lyzQAdEBERAROSICqiqAiIgInJED1REQEREBERAREQFhNNDhsPJiMTII4Iml8jz+Fo3Wa8P2840TIODYckgDPiOQeeTQfL+Km634+PK/wAPD9pOLycV4niOISHSU0yOryN2a37LqhA/GRhrHOztIzGuR3PstsRa6XJMabI7JXR3L7LCB/dYedzwIi490M15dNzarLTxSUBxiiNMiGUDLy6+66bDxh7i4nLe2i5OMmLmtLa71ziC7eyOfussBhZ8TOyHDNzPdzP4epKuo5/BuEftTiUMDZS2MyNbLI5tZGk6lfTPi52fwkGLZiOFwwtwJia/CSQsDQWNAEjSAKJBIN9LXkopIMDiYOHwvY0OcO9kDw3ORrlJO17e693WOxXC2/tDgkmA4PjwzHQxPd3rGyFpbiGRvJJHgOejzYQFlXxiS4XlojAbeoOt+4UEBrMxj3DmKr9V3XF+HzYDiGJ4dMQx2GkLCXDSQcnA9HCiPVdQ/Oyu8kcwOGnM0qMw+2BscGQjQvaaPva3fLFninxAjJALcrcwd9iuOe5fQaH2N3OF/oFW20GQTsa7o0G6VRzwZIn54omvbYBklPif5ZFymcZcxskMTMNPM5hDfnDUUZ5kNBr0DrXVwsk/tRA+RgItznXZ/wB9FsxWJjx+Igc4wwswxpuFhhDTY2eT+K/PVQc9ofDhoWyYoF1kuirRrutDSujRstGMxGUgjFulL/rJ0F86WqZzGgkWZHGy55zG/JcHEPMb9crn1yVGM0zC8CIOLAdCdyeq0F+V+jiG72Vi6R5GYk2sK8NE5lBtjmIJefFZ1XJixzmuLz9R5rhBxbVaDmOqzH1FuwtB2kWLylj3agcuR8lu/aMshkfI+3uPiHXy9F0wJLg0a0tolN86qkHdR4sAgdW6raxzHHK11VqBa6ZshLmEnawt8c1+PNuQiuZPgYMVyyOu2yR0D6HqtcnDMTA79zi45IyAWsd4XeXktJxQigDyX6HQsFkey5sL45IWtiiEYDdGjf1PmgkXFuLcMd4i8Mbu+NxIP21XpeDdusc4tDMeXbDJiKc0k+e4XnHF8erHHfcfxXXY1jXvc5o7qcG87dn+oVqPr+H7ZljsvEcI0i6z4U2fXKV6TC4qDG4VmJwkrZoX/S9u3mPI+S+CYTimI7oMe4gjTQ3S9J2b7VO4HxFr5ZHTYWahNExu4/P6hWD65zXx34oyzSdqIIMSI2QmC2uFn8RBvpei+wMkZNEySF4kikaHse3ZzTqCF8f+KbZY+1sWaI9z8qDodHDMdfXqFlce3+GeHEHw+wcpJc/FyyzPJ/zZQPYNXpp5xhcLNiHbQxPk/wClpP8AJed+G78/w34RuQ0StBu/7w7dB5LldtcXHgew3F5pnZWOg7m/N5DdPNEfCoA7EY10jpGumlcc5AqnONkhfo3DsEeDw7G1TYWNFf5Qvz72fwzcZx7CYc20GRlC7uj16L9DEBppooDQDyU+XTf2YIoirmIqpogIiICnJKRFakpEUQVU91QqCqIgiqJsgKoiCoiUgIiqAiIgqIiAiqIJyVCIgBVRVAREQEREF5opzVQERVATkiICIiAiIgIiICKhEBFFdkBFEQVERAREQE3ROSAiIgIiwmkdDhppWNzujic9rTzIBICDpu0XaWHgbBDEWPx8gtjHatiB2c+v0C+V43GyTTvmktz9g86lxO5vmuBi+LS4nESTzzOklkcXySE2XE81hHjGSQOjeczQMwHRTcy108fyeXj4b4Z633/ZyHxRPxONY793PBkfG4ahzTu4XzPJcXi0gGGLg8Ekno0u/wCXktTsWcFisO50zTKLdDiA7MY27EOb+LTQXsFycbhTxrCNmwUbIMSG5nMPhjAA0DnHUOdqRyJWnN5ljnTYkuLrrQFd7wTEHD/MNGj3MLrG5rYffVdPHE6OEAghwPia4U4FbWYp2FeyeNodI3QtdqHjmD6qD0mB4JPjMuJxj/lMEx7e8xErT4nHUNYN5HnkB6ml7vhmMx/EOG4/HzYB2B4hgZIgIYM5MczASwzxHQNla5wD27Ea6FeX4l2ml4iMHiuGz42/lhFFPiZA84SMaGGD8gsan6uQNLndk+2kvZjiMc02LfE1jDH34j79zmHUxSNJt7LsjW2nUc0Zx3PxE7M/8LHxHDQPkfh4WyFzTefCnYnzifbT5Udl8tmZmbcg0B67r7V8P8Zx/EcQx/EvlY8PwniMsj4MPM0uf3bxRLWnQM8juvmXH+FRYLH4hkLIxHBIWSNiOdsRuhTubDyPI6FRt5txidRGZtbButLY2Bv43yZqsUAb/ojQLPhBaN3EUL6KtbG429z3joDof5qo3d0YMGzFzF8cTjXeObXe60WxnqN+izhMGFg7kwse2yTIXnM89b6rQ8RnEU6ds/dAOa9l1Fe8evPqsZcTCI/BExhqrFn7WqEskrHkte0aGjY0B5eq4Q0fqRqhkc8ZRZBN68isRQfrr6FQMwrXU2hBvQaFWiXeFup2VcHAjPv5lBCLeKWdXmvdY1qCCNtaVFiQ5uSDIEBl8xsVm11aH8Wi1gmnaDKdlmCaGn07oNjCRE4b0tl5Sa2yrCiSCCNR91QcPLmPfvZIwf3Y38ig2xST4Z7gRk0oua69Oi5EEgaQ4GgQuK1oDQRz31XIjJDLqwUVzWuBqzyWiWMPjzHUu/grvsKobrKgCPFo1B1UjO7lzi8w59VubiHU2nkE/iBFhbMRCXsJqqN+y4jQHBrA4gtBI1vN7K5qPq/wy4/83gZeDTHxYYGTD2dXMvxD2Ovuui+L0Zj7Q8NxDX25+EyiN+rfC47D3Xl+A8Um4FxrD8Rgffy7wX1XjadHNr0JXsfjCwS/sDGYV9iVkoa5uzh4XN1901ceh+F8xl7BsBaWiLFysAdqeRJJ56krq/izxTLgcFwiFud7ycXMQfoa0U3TmbJPoFyPhA98vZrH4d+Ud3j9CDoMzATpy2Xzjthxh3Hu1WMxQkzxGXJA0fhjb4W+tj+Kg7r4Z4BuL7Sxyv1dA7vD/hFX/RfZrskleM+G/BRgeEOxz4skko7tnXq4n3oey9mpn26fk6nj9f8Af6ERFXIREQEREBRVQ7oNXJOSIgKqIEFVUVQEREFRTmqgoQKKoKiIoHqryUVVBAiIKoiqAmqKoCIiCqIiAiIgIqogqqiqAiIgbIqFEBERARFUBRVRAREQEREBXmoqgIiICIogu50WMckczi2CWOVw3Ebw4j7FeM+JXFZsLwYcPwrzG+cB0paaOQmgL6aG187GCkfxPERYLEy4aTh8IdEyJ2Q1VudY8yg+8rrON9ocF2ewzZcWS+d/9jh2HxP8z0b5r59wz4jcZ4bJhYeKRx8Uw8kOYvkOSWM6jVw+rWtxa6LG8QxPFeIyYrGyGWeY5nO5DoAOTR0Qea4y7EM4jPiJI42RzSF4bE2mMs3QHILXgWnFYoNjadiTXIdV7KTh0OIhZ8yGvw4kyvyuou03Hkugijw3BWzMsd48m3Xt0Aroriuk4i3LinFnXRb+G8Q7t5ZOzvonH94xx+voLXGx8omxBc3nr6L2XCOw0OJ+HXGeOYnECHHYB8DmQOb/AHb3UTfI7KajquKsdi4p8VI5smKw1fNyA0JYyaaQOZGxIXSy1kFgH0XMw0rm4uFs7WyhrXQFknhYGkGvF15ri5H92Q1ug5k7IOVwPEkz/s972sbiHfuXvNNbKdACeQdsTy0K9T2R7GcQ7Q8fycQw0mGwmGkHzQlBaXEHSJvUnmdq9V4OQF13S+h9nvixjsHwAcHxuFimxEcRhwvEHSEPYDoA4fiq9CiR9F4nI/tFiXcD4ZiDBgGisRPFoXNaac7/ACAjK1v4iCT4Qus7UcV4N2V4LhuD8P4dDO511h5gHB8Z/tDI7cZhsetaaLj4niDPhz2Mw2FLWS8Xxg74xZswke7bxDdrRW3Ur5ljuIYziWJlnx2Ic/EPdmmedB6AcgOiDbxjgZwMMGP4bN81wbFkjDzu3jeNXQSD8Mjf/wAhqF18XyeHifLJ382WvCzwgXycuwfiJOE8Cn4W97mv4iY5pYBVMY02x7+eY/hHIWTuurc5kXdvga8PfYe8nTL+X1PNFxmJIpYWvniEV7d3pn9fPqVxpcSW23DsawfmqyfcrKZ8RstbZ/T7Lj53OGW9EEIdQzH9VnYygg6rANG9+yyFZSOiDJxdVh32KhqhufJQgBu4Ky32HiQK/EsiQc2nLqsbIaBY3WWhABOqDIA5QBSzBOWgCTvosG+HldaLbELcRmEY5uq8vmgyeDEGuZEXvJo3oGf6ra97myXMxgNVTAB/BaQTFbe97xw0a4tqvP1UbsBdHc9EG9hAbYBbrrS3sB0ymjutDXGjmAHKluYGZ/qIFIN11R1vfQrPKKA1JdqVpacrSHO1PVbB4fERtsiq5oe19HSqXAlY2GcuLS5h0NDXzpdiBfh0BBs+awmble2RoDnMOYaaFBxJInMY12UBxb4T+QfzK7LjHGo+JdjeC8KxLj8xgJ5QC4nWIgZXE+RsV0XWYV0URc1xJcPE0Hz3pYYyMx1JRMbjbnEWTprp0oq76Meu7O8THAPhT2gxEc5ZicZjG4LD/mBya69MpJtee7M8Ml4pxrDwYaMiMyNjtxsMXXfOyv4dBgmlowuGlklabtpMlAk30DaC+t/DrstJwrAt4lj2luInbcLHCi1pH1EcrGwWN34dfx5mfq34/wAvZwQRYXDx4bDtyxQtDGDyH+7WfNVRacv6iIiIIiICiIgIiIrSqoiIqc0RBVVFUBERAVUVQFVFUFRRVBUREBECqAiIoCqiqoJSIgIiICIqgIiIAVREBERBVERAVURAVREERVEERVEBRVRBUURBUURAVU0VQfPvibHq2SgM2BNE8y2TYfdeWiwzH8QOPc57ppnthdegqSEke9tI81674lszuwYGTMcFP9R5BzV8/wCJ43EYd3dROc2N8eGnokUXx3l15VZ080GnHeDA4XK3+xD4ni9nXd/ZdjwXBnFd64WTHGSaGu23npa47MZhuKMf3cjMO6d1yYaXRtjWw7kudhRDhKjxHzOBc8gCRo8FE75vb7IqdqMPNg+C4bFueHwiUBssZynxDRuXnt9Q5bheSxGMdiWtiyNEjTWZh0cud2qxkuK4qP3b48PA0RxlxcQ/q7Xr/BdTg4o3WSaIIu/XWvNEdpwXhpzMxUkRe7McjTQBI5knYBe94Di8PhTBDPNiS3EYsYPiMeUGCWORpLJGOOuYGibrkuklaJoBh4qDX0GxxjUNB8LfPr7rsuzWI4iOL4rhGC4ocJgZoHNx9DvIS4tLQXgA+EEtBcPp35IPFdosDiOE9o8XhMUWvfDM9xDz4X0a25nT3XXs11kJF8gvfdreEji/CuG9q5Ie/MEzeG8cjjeCWyN8LJQRuHNGjuZb5rx+P4VPwrGzYXEVcZFO/O0i2uHkQg6x7GWQ0Osc70XHeynVuD1XMe38xC1OY29CSelIO64d2gEvCouC8eEuJwUF/KYiMZpsDe+S/qYebPtSxc6DhuJDYpoOITNcDEYrMNcnOuif8p57rqo43uJa0N03BNFbmNDG24F/UXp7oRvaG4rEvfK6bETyPL5JHH6jzJ/3otOeSB8rJI2tBdpH9QZ6dfVZSW+NwDmsJo9LHQea1SPNHICGdLQa3vc7QCh0Cxo5tfsmpFk6KgX6hBAN9VaFb68lQAb/AFUArVBWltW4aHkFQaPKisdxZFK7t8wgyvawqBTt9KUq230W1sTnuDQ0nSzQugEGIJouySPaPqEYsrYI452tpuSe9STyHM9FsY/GicNimYyOMAh4eGhvqRz+5WuSRlOjgLywm3ufVvPWuQtAdlAIjfnH5yKv/RZMaSwNvmtWUUKOh3tbW/2h180G1tObruDei2UPCWnW/utLNN9b2K2BzQ7QVSDe1xLqrUdVsDi0h2vra0AgEk6Ws2uoAXeuqK357sOGh1WeYEXyIpcV0lDxHQn9FGyCZzo++dEaoFrNdfPZBcRI+DCOMYLmtfnyCiQetLV80zFQU6MPafG0keM0NWA9Dz9AuY6BrYswcHG613qt/RdKI5oOJNYwNcw5i0SHw7ahB6r4b8Jh4t2yacVh24jC4WJ00jJW6X+DMOt19l9tJJJcTZOpPVfD/h/xb9k9p2SCNxhniLJmtdZyUTm16Va+2YfEQ4rDRYjCyNlgmYHxyN2c07FEbOSnNEQEREBEtRAREQEREGlEVQEREFV5KKoCIiAFVFQgKoiAqpSIKqoiDJLUBVQEREFRS0QVFFUBERBUURBUREBVREF5IiIKologIiICIiCoiiAivNRARXkiCKqIgqioBJAAsrynGe3uEwM4wnCcMeKYw3s/JEyuZdzCD1ai+V434o8YikIzcKw+XQtZG6Q30slZ8K+JXF8fxBsDsXwvuWgvmlOGd4WDeqOrjsBzKDvPiG0B3DpDlGaHExWRto138l8p44D3WEfRAfh2iutL1PavthiOM8VwWIlY3DYTBvqHDg2GA7ucebzz9KC8/wAcwx7ppAP7hzmOzWNCbaa5CuRKDzjHFxLZJAwAWXHX7rmYHj2PwLrgxDspu2v8Q150eem61yQQfLgskDnk0WtOoPmOi4LmlppB6bD9pIHMDcTh2s11yDwtHUNOmY7WVh+0OGsjeYWNa4i67lpPQC/4nmvPscMtObfQrM93ZLW2ANjzQe24HjoJOzU8z32zDythnhjbU81g92BLvGx2uYjpQ1IXM4b2ox+D4jhsU50UUeFsYdkEAEeHYdHMDPxMcNHNN5hrdrwvC+JO4bju8s/Lyt7vEMH4oyQfuCAR6L0eLwk3zzcDhmSTTygPhbAMwka7Z48iOaD02MxoxPazuuwuEhfheI4dsfEOHxyOlwjrNuZmIGVo0IO7Dsuw7VcDml4Vw3h2IwXd/KNezAYyR1uladflpXbZmm8rjobFbr1nZLhUHZLsh3/FjFhe6jM+Mk3DP6nYeZXdNxjMfwIzcQwpwUU8Zd3ExBc2LdrnjYEjXLyQfnDGYLuYmyvJDnFwMdU4V16FddlF2xhA817nH8Kj7T8Ex/F+D18/gHE4vBxgnvYboTs50BV70vElxa4E2QRoOQQZNgD2gtezvPyKxtt4jOcvOjQ3qkUb5bEIDPMmh7nktrpXxhxxHduyjW3bjyI3KDW+FvfndjmAtewuFNd5HmDuuM8ODjmcDXTVbHxsa39yXBvIPOv+q0UAaP6IKXFx1rogF8t00GxQm9OaCtFHXQqgcxy5KAaUmmxO6BVmunRUaik0BpNiUFaS2q3CyLg8iNj3sfduLdbUcXsLM0bnX9IA38ludMYmNbHE3DmqdlBDnHz8kGD3lzGRhjWMZqBzJ5klQAZtNQsCb5Xe6zaBfOqQZ5fEKOgWbdT0ICwbYPXRZAjMdNSg2McPss2uBZvztaQQBY25rIVlA68wg2ggNIOo5IX+EgkA8zyWuszfD+H9VsZE+Qtbnijs/U7UV1/kiqMstsjmAk0A8OY36LmxxmPwSGyD6AeywieBHbWDONc40K2NskFpzVv1QbDZbobXVcRj8N3q05gQuxaOebQ8guPiW22966oNvAgx3EoROWlr7ZIWs11Gn/dfUPhvjXScAxHDpXXJw/EFtf4Hbe1gr43AXNka6Lwua7NTXURR/RfRuyGPbhe2kJw9DDcYgDAb2cNRfnY280H05ERERERAUVU5oCIiAiKINaIiAqiICIiAqoqgqIiCooqgoRRVATkiqAiIgqIogqImqCooqgIiBAREQFVFUBERBUUVQEROSAiIgIoqgKqIgqnNEQVERBERBZNDc7IPM9uuMP4bwaPB4aUxz49xY6RppzIWi5CPM/T7lfIsfi3YTAhusYx5MkoZ9XdjRrPIL03briJ4z2rnweHdcbHjAxO6ZTcrh76ey8V2gklxXFpXQNBgjAhhLbpzW6WAgxixnDMtPhmgeNix1hdjhHMdG5uAxGFkD9RG7929zv4LzTsM4DxXmPJc7DcJljYJsTG9zXfTGBuR1/og7LiMMr2uZIHRysBJY8bjyPMea5WGlZxPgxiLQ+WEC3huo/Lz8ROxPJdViGXK907CIyKbGdXffYLh4bEHDSB9AyMJyBw013tB2AY6T9w2OVjWjLLMXNa2r/FXIfdcaXhzDE4wZmyMcWuDtjRXKwXFcNhJG95hm9yJO8c4DMQToW63YrkV2OO4fhnsM3DgY3ZcwI0ZIDsa5adNNNgg8oWGNxa4EeR5KVvf6rsZ8OXRte9pDzpXIrhOZenTyQaR1Xu/h/8AEKHsw5uC41gvm8BZ7qeMDv8ACXqQ0n6mE6lnXUc14gNrdYuGuiD9Q8I7QcH7WcJdjOF5sVh8PM0OZiIsuSSraS0/cL5h2z7czcexM3CsAXMwTX1iJiadNR28m3914Psz2k4h2X4ocXw59skb3eJwznEMxEZ3a7+TtwdQu/8A/C0vE2Mx3ZN4xfD5neKSeYMdgDu5uJJ+nLr49nDbXREbeAMx8XHGY3g+Nbw44FhxE+Nf/Z4WIaOLh+IG8oZ+Iml53iONgxHEZ8VgcP8AK4eWZz42EbAnTTl6crpdjxfiMIwH7D4DK+bhsbxJisc5tHHzjQPo/TG3UMaf8x1OnRn919dEjkdQgzMWIkdnbE4tNkVtpusZHsaxrHESOJuqruyOfnfRa8znPtrnAeRqhzUEucBwYw6UDWrgipLJnN7EdFjXMm0Lm9COqCgbvVBRV6hBqdtlfM7JuPJBBZ5LLd3JTdWsup0QAASSFk1ri4UwOLrygmg5YtaMwBc1gP4jssra6nxOkdlPNug80GcWIxDIHsz5QdOlf6+a15iR4gdeaj3ue7xG62UYOe6DIEFh5LM7UDqsQLGtLMboMgaINpempNnmoBqb5bKg6HN1QZ1QA3BVunAA+wWHiAaD/FM8ZcY3F2uhyVbUG8Mm+tuGcWAAh50y61+q2sMMMuWGMNFDWrJPP9VoAkGpkLwa3PRbGOLtqsbUd0G1rgS6tNVsaSDuCtDXvJady7c9VtYQTqKKK3DUZhqSdAFhKMzHa7jU9Fk3S6f9Oug3Vc3MzwbOGp6oOqDYRiSJSYw4fVrV+a7zhmLI4TBLhWEScKnGIkLeYLgM38B5rp8W4w04Nsc9ev8AquXwWV78JxCJ7yIjDnJJ3I2HmEV+g45mYiJk8ZtkrBI2uhF/zVXnuwnEDxDsXg3PNyYYuw7/APlOn6EL0KMloinNATZE5oCiqICiqiDUqoqgKqIgqIiAqoFUFREQFURARFUBVRVBFURAVUVQEREBXmoqgIiBAREQFURAREQEREBVEQFOaqIIqiICIiAiIgJzXSdpe00HZ3DxgRHFY2c1Dh2mr8yei+f8Q+JfG8PM6MT4cSbObBAKiPSzdlB9b32XC4zxQcF4Ji+I2M8EZ7oEXmkOjB/1EL5Zwz4l9oJsXHA2ZmIMjw0uxUbQyME7ucKoDcrte03ap/HZcFwaCOH5b5tr5Jm5h8y5gNUDq1l6i9eZpB5Bzzg4sTPIc/ykRw8ZedXTPNyEe5K43DYe9hOJxFVlysHWlhxEPkw+Gw1lveSvkeXaDNmrfyWyGKUwERSQtZC4tLnE+E112/1QaX4nDxOe+ENmm0DG5brz6BbHxzxTQRvxodK2MOhbM4PY29aDR1Puowk9zh4w1gidckj3B3enfwj/AGFvjiwkM2Q4bvI5WPziMeK9wb6g80HGw+fD41s+JdG95H70lp0B0II5eu66bERAC4Sbs00j+a7qZog4sZJnte2Rgktuzg4dP4rifLF2DdK02G/W0bhB1McM2IeYoo3F+5JFBo6k9F7zDN4aeCRwwYqUmFt6tJLndK1BaTrsCF56GKNzQ15eTyyu1vpXNc7DmKFrhFhBFiI3Wcxd3g9rQTimBxGBmkOKjDGO8QLKpprnzo/xXUzgSFmRv7wCm5fxf6r0k0eJjAnx7ckMxIEUu763scueq6fGYZsb3QQSDuySGh50Yd81jkiupLC0BzmfUOY5rB8WZpJaQR9lzcrA1keZ0jSMzherfRYmEiFzs5LbFdR6ojjwYYOPjcRppTbtdhhcLBJpI4lryBIwyZGuA1p1b+VrABgaCC8ho1cCP4LW6Wi0OYctcqBKDZK9sDQ0xtkaNteXtuuHJMx+ga4/lHIIZXAkACui1Oe57hQ0HQIMhYGZrLI2o/SeqjgTrRUsF4shoAu+qXZs3XRBNTyWQ/QIAelJqdEFrT+abCgErTX7ITXLVA12G6tE0CSf5qXR2s81ibcC5oLht6IK17cxY+PMNnE8vRXO/LlBpo5KW00Nbqib3Q+iC1/3Wf0jzWOwCyHK/VBa8O6ugPkoNd+iDXRBkB4jqg1DddgsSdDZ0BR7mteAc56hun6oM/3jvE1oNaEE6kDos+8Dz46vYkClqAaADGCL3NrIuDhdUbQbIySSC77rOM5QQ4VXRatWkE7HmswR4witzbyUNwdFtBzUHjZccVQdZ03C2BzSBYuzog5LQ1pbuRzJW02bIOg8lxmP8B0NWt9kjnoOfNBxsTGHxkEXbSNOSvBJ2HizXYpsbopWt75hOjm2BRHLr6rN9E15LgwxPOMcAG/S+hXICyUH1f4Zzd03i/DHnxQzCQNO41LSf0C9yvl3Zbir8P28ws+I0ZxbBx538nvc0Au/62/dfUvI780NFE5pyRBERAREQTkiIg1KqKoCIogyRRVAVpRVAVUVQVFFUBERBVVAiCooqgKqKoG6IiAiIgqKKoCIiC7p7IiByREQE3REFUVRBEVRAREQETmiAuNxDiOD4VgnYziM4hgaQ2zqXuOzWjck9AuQvkfbTH4nF/EPFjHB3yPBGt+Wgug57mgtP+ZxN30CDg9peNSYnHcQ4lO0iQkQYdl6xuOpPllGi8nhZ20B83ExzjZbKywPddjxe5Gswjn5jCM0tfilfqfsF1n7DfI5rYHAl3InQeqDuIZpIG3NA1kMrvDPAM0Z+yYvE/K47CSAECN9G9d9/wDsuHh8M7hkWRhdOxxzSBjqDiDoK5C+a4/EZhO9kjT+9NvkIJOVxOxvn6IO5xvdCSGY5cTh3SkZY2EZ7GrQ06DX9VcRhMmFL543tjYW5oWOBiPTMBzA5LpjjmujfHnmc2WiC59ZHc9Odr03BZDLw9s/eMp0bg+zVG8rgeXMfdBqnjwk0D5Ji6I921sYirWTYHXr9tEbO7h2LgjxUcUscTCYpcrmiUE/dvRbpcO/BcKkZjcAZIHNayPFtp7W+LwnN+EkcjusMRjMRhJsG9rO67p5McrW2CHfhJNijWxRXU3hcQJII7hzO8DDq2J97XvS40bxHHIx7bcHZdRdG6XL40yZnE3yYrDMjmDgS2NlRuYRYcK0O9H0XAfJFIHvYO6OazWti+V7Ijsx/wChdJ3bYyzQvjADvfqPVcjD8aOHp0crQ8iiANJB7rqW4kYctkhcSQbsgV9lsPECWuHdxtLnZmkbg+Xkg53z2EyPZiG98G1UZe5lDy/h6LgyzMnjlic3JhQKjkdoRWwJG/S1xxipzKC14cay+IA0Fi/K2OXvpAWgfusu2YeXRBpvM0EHK6qPmoHloomgdDqtZLbu9OSU0m7IvqghdqaIcehWBeSTrR6qvBaaAr9VjuToEGNW7U6lZtABAOjTuQgABtZWzI9rgS81lN6N66c7QYZKJBqwaNHRZDbksaa0ABZNHMILQJ0JV16pWniNIDTTogm4t2iuwJrdQC9XI7+GwQYudQ8Q33CgbkNk2T/BAGyEkAmtbWWhGuhQCb6LIWsR5c1fPdBkDZ2VBBO+myx2bp6LLp0QLOUAaK9CNualjMbUsNc3M0uvXfQoBcWtdRbrvfTyWQkeQ0PcXADbkFgGgNIAr3WVbeQQZDSzem4WVh1X6EqNobiwRtdK8gRY6oK0iyDyKNNt1O6jQK3olBYYUGbXDKb5gLPPl2239Frq60RxrUimE6nkg3tkdnJAsHWluZIaBLSQBWi0YeITOvvo2MrQkGj5ClzIMLGxrhke5xqzmOWulIJHGZ3fVlBF09pBPTVaJ4XQyxTRAmqa4B2/T2XaPcXjNQs66clxZ2Z2PANEjRFc6PI/hFsnacVwyTvIXMupYHuF0eRY+j6OPRfZ+GY9nFeE4XHR1+/jDnAcnbOH3tfDez/czYo4RxDjO12H7thrLnBDQP8AmAX0L4YcUkxPDMVw+Y+PDPD2gDSnaO98wReo90iIjIhREDdQoiApWqqINSqiIKiIgqIiAqoiC80RVAREQVERBUREBVRVAREQVERAREQERVATmioQEREBERAREQVERAREo5S46NG7iaA90BFwMRx7hGFNT8TwzTtTX5j+i892x7Z4fh/ZoT8Dxcc+ImxDID3Tv3kTTu4NPPkg9jRBog2V1PHO0nDez7WjHyPfiH/2eEgGaV/tyHmV8zj7T8bZh8RgoON4ruLzz4p5t0A/K1x1vyXnRiMTxLiIg4QyeTF4l/dxyFxdLM4+Z2/kEH0nE9v8fLgZp8BwmOBsT2skllmEhhzXlBaOZr0XjMdxF+PxBxeMe6eZrH4l731+8cPCweg6Lu+JDhHBOC4Hs7wNkMs8NTcU4iSCcVPVloP5G9P5krxGHxT8RhcRE5zHCONzQ4uDWhpdep5+XRBqhZJNUkx1LjI935nnVb3PtwfIX4cNbYc92WyDyq/urDCJ4AIcMx80RzPf3tNaNrIOl+i5uE4Y2LGRzTSyPY54EwN5YwdW2OY0QcHEQuML8RhQYcHI7O3vjczT0J53W64c8wmZbrLutrtf3eJZNhMb3mEmMTpWyPOgymyD1aR/AFdMMoY/YkUB0Pog1P4bM6JksM8BjfYIc+nRnzHPyIXf8JczD4SKLCSNf+9FtkGVx0112IK6RzA4h7TQ3I6Wu1wmGe5maCnSQs70gnKSL1APPRB6DCOcxxw2PwUkjHx2+CNwDZGE72Drtv1C40uIxWEwD2yRyS4ZsjZIp5GZWStBLfEKq6NEH9VgJJWwxYxosYYZ2ua4OABN04ctdR9uawix2Nla4cPfTZrD++IEdm7Gul9B5qjjcUhjw+Jw0vD8Q35WZjXPidJmOFcTRaDuWmrBGy6LLK2WSNrho4tPRcnEswcjLhdLCYwcwcyxn6dQD+i4Uhp5DLynUa2fdQciNkj7bqyUHQ6UVnK2aPKzFhuZwsWdSFqHezkPa10r2jK419luLcSyFzpYHtido5zhmF/yKDTP3ZLWQhwY3W9yTzK15BHhu8nY53eWI6OjT1K2RwiXP3M2uW/Fp+q1OewRg5A4u8Oo+nzCDS0i/FoPJShzIrqq4MzWbrpay/dvH9oGD3P/AHQQGQCm5a8hupqdm/osqcynMcCeRHJHPlkbmfI94BrMTzQYHY8qWIBeQB9S3NexoDiwSOvZ/wBP6c1izK4P8Tg53lof6II6JzHASDL6qtbr4NfMbJbWNLDCHG7Bso0Ok0Da8hsgaXWtqDzKbbFBt5IHQlHNc5oLBdH6vyrLwczY/goGHO573h3IObsUB2aidSNrUvRHZrHMIRaABQVGg1KVRGioGvkgXTfdHbik5Enmo7MxwcWOIvpp6WgE2HNbQdytRgJbqSdFk7JmtrA1xG4OiN3vqgoFgAqg23/RA4t1rQKtJB1NhBluL50gacpGlqDUWBSyAJc42EErXkdNFHCjl11NhURucKBFjSrXJZgx4vmmZg0BxySjTkLI280GpsMj8znQyljfqe1ujelrn4PCMc5rWmSStZGvprAOlrBmHa3DZjN+7LvBG06/5r/RZSzvyxxCQOaBoA3KCfNBuOIkc+jGMxrKKGVoG1DlSxzODxm1vmCtBJFt0vnlNj0QHKRuAUHOidTSCTV7FQsYZMslhpvVvJYQvIunWCFnIbAcOaK4ZldhcU90bcr3Cw5mpDhqCPOwAvY9neIN4f8AEKKbRsHEw1zsv01M29B0D9PZeOxsroYI3R5Q5koka4jZ3JdjLPIOGYDHQPc1+HkfCDWrQf3jPbVyNeOz2+6VRo8kWjBYsY7h+GxbarERNk06ka/ra3IwIURARPdRBURRBrREQVERAVUVCByV5qKoATkiIKiIgKhEQVERACqiIKiIgc0TmiCqIiConNEFREQFVEQVFOdBYzTRYZubEzRwiruR4b/FBmi6qftPwTD2JOJQmt8lupcSftvwKDfEyPNX4Yj/ADQehGoJ5DUnouHxHi/D+EQMm4li48PHIcrCTeb0rl5r5X2+7YxcW4lFw6HFYnC8PbGHhzBl7x53LxzA2Xn4yQ4YXiETZZImXCQ85cQzyP8ASkH0rjHxL4fh45WcHZ8zI1t97Joy/If1XguI9teIcRDpMe/OwUGskJynqMooLq5cO10EBLmYZkbBnA1a5/MriPiw0pLnGXE+dZWN90G2XtJISyJujGv0yDxeVdei7k/MvaBj5Iy+GPvMRLlH7kflBH4q35rpsJgG4fFQYqbBiKNsralLvC0nY66FcziUn/Cx4YOc/wCbxBfLlH10aHkfZFcLFOxPFQYOHxdxgm2fEaB6uJ5nyXIwngxTII52SPaPqcfBXmRsFtbE/CZoBiHAABxiiYM1Hcb6c9FMTw92Hw73zRPdE6xCGxDLZNjOR5A+4RGQzOcYH4ccQu2xGFoDG+fXTzXS5/lcTKHxsfnaWDNs3zXctliGJ/4WNrY3Ma0NZpXW/MlcXHYXDYnBNqQw4uN+ltJa5vMHoQg7PgeOk4lK/CNYx7zF+8blAt45srqP4ea7YYNk/C5pYX91bu6LXNNOLtz5BtHXzXTdl5YuHB+WPNKA9zpObjloX5BevbiIJODcMgkl7pr8Qy2NoFhA0ffPzKDpOKtxcGNwLsVA0ujbGyJwHeNMYF2OZ9DrRory/E43Q4ktkjayOUiWIsIIc08weX+Xlsve8TwpjxEUsZknYJO/bHG3MCC05yCNHFlWQKNbLx3G445YmzwSGmSOc5o+g7eNvMEiiR6Ec0HUxkslIIzNqvULmYSaRrrvLXMHX7Lr2OIfuNTzXMZVukkJLNCQzf8A0CDlQTzQzgRyuicz6JGnkpjHd3KO5azJIP7O+fXyJ517LewyT4eKDDwxl7T4HOoabkE3stjMTgWxhpwzDYcZazNcT76ADpzQcTEYYsiYJA2awXYhkbi3XkLPQdF1ZaCC6Bwc2swObUDp6ru4RjGQvY2FjHPb+6c9gbbTpev8RsV1WKaM8mYRslj8L2MZQOn1A7aoEcpkyNe42NnMvN6LluMkMZ/dvZoGuiy3Q8yNF1kZbWpc13LLuVzYyyJgkY4unO2bYD+Z/RAeyVmD7xsDhE+TWQt3d+XzpaXskbA8RNeJAf3wGoyf91udPPK1uV7i1h0aXXqfJaJ8NPABp9VuGVwqhuCf5IOKa1zEeoUutGOvzVOupAorHQGgD6oKBr4yWj0WQcR9A1rdY0S7U69VQKtBXHLqa10rqpbcoaPCByKC+8AABvkUdTdxaCa8rI6clSCG9AoA4gnmgs6FxKDNo2G6pGllA0Cr1KpYxsBkkkLdaY1gsuPXyCCCNshDC4hwFkg6e6zkYyqjefDyIWbXYXLmdC8Sn6iH6X1payLJ1sDmUARkC3NPQG9LUyVdG6UBINE6IW1qBXlaBWtaWeStiiCEG2vLZUAPY/wvflH4OR8/JAsN0c8tvYgXXRYljwynvzG981rI5wBKWtBIrT/e6xIqiNOvkgmlajVWq0GxFq0CD1VrTRAtUau8qUGrhXNbIsM+RhcC1ozUNdSegG5QYN3H4T1Oy2Mhkc45BG6/wmQNsdbW6LCzOYwOgaWSPLA5zxTqOut6LYGMhP8AYxmycrGigPf8XqgseFjfEZGQxQuY4W98mYXWja5nc2siWw4URtY0k05zyQdfLotLnAU2RwcN6aNWrF2V30NINddyg2OJkaX2G5dANrUa81TLA52VrL8waHO1UzPHhJ25jmgza4FpqwAs2uqhuD15LSCHXoAfNZBxG96IOUwgGgTouVmLm6rrg4uaSBqDuuVHJ0N2LRUxLS6FwAtxbTR5rlcPaZ+A47Di3XGJoqItz4jmcSOmUuF+S0HUa8lhwfEt4Zxl88uQtYbLXC8w2c30yl36IY+s/DzHtxvZFkV2/CSGM/5T4m/zXqF86+HbncL7S8T4K9wLS05D+bKbafdrgV9FRfL3RFFUZRERARE5INaIiAqpzVQFVEQVUKIoKgRFRQqoiCoiICFEQVFFeaCoibFAREQFVFUBERBUCiyAJNcygiwmmiw8D5sRI2KKMZnvcaDQvMT/ABG4FBxA4RrcXPTi100UYLAR01sjzXn+2HaeLjOJZw3BTEYJo7yRxBbmoWXHyGw80G3j/bnHYx0kPAbwuHaDeIecpPvy9AvBz8XZI18mO4hJiJi7Vrbyu++q4HGuIGdrG4Rjo8KwZWk/iPU+a6R4vxXvqbQemj4xwnDePDDEtkcKcJH5mubzB/kuJLxfh+Z7GYGg69XSF1dPVdEd9SqyJ87ssLXOPMtF5R1KDt3Nn42GhjA1sfh70jfo3zK50WIMOHjwODY7FOiFEkeEdbP5R0C583dYfDyiDwxwYVsWHFZasau13P8AVcDHsn4fw7APjdWEc45Y4wQWu/xu5k76bbIraeF8QkjZi58OTEXNAxWJGWKO7oBvTQ0Tposw+JrxNHi4sR3LreZ2VG7pTRufJXEYps1YiGWeRxiaJIppaYaGnhG4Gleaha2fEQyuYzvTlDi1tACuSIy43PNLgvmHPmnLZ2uE0hysBPJrBy8yuPHI+bignZI7JCxr3Pb4mkEUXAct9l2mMjdiexmPZHb/AJaVs1AeJzQaLjz0FegXR9l4sRie0GEfDG90TXeOQtORrfXZB6Wfh8MUcckIZh8PI7I9rB4c4aDnvzHXmt4fI3AtfimNfh5iMO1pJBzDY6c2g7+oW7EYYx8Nkw9XEyVoieR9bi7UD0HupPhHSPwuEwGfI6My9094Pjui5p5AgbeSK6PF4N2FniaIpGkUYnOA8bCNCCNHWfdcPGsaSHjN+8c42evr13XoZoPnsE6U4Z73cPb3lxHWZlnOCOrRtWo8152d8Xdy/LuM0AnHdSPFEtqxY61+oRGeHb+9hc1+Vxb4hyoL0HDsYx+HDRI2OSTEMkbmaLaxl6eVk+68yH5HiWIAAjb8tdF22HxLS3DzSBj2RnIWgC7Ov25Kj2GKnlh4k5k7YYJcJIx8BjPdtcHtId5U4Ea9RuvL8ZwIkkfLisEIocW5zCxujopmi2+H8DiLofS616SF/D58C105DWuf3M0bSGmJrrIfETtRGoOh5UuFxDhz+IwtbBjnyxYiP96ZmgOEjQXMcCN9tOetKK+cNPdyuB1ANbfrXJcnCvdRaHAeRG4W/jcWIZxPNO+OR8jA4zRaB5Is2KFOGxB1XEiIDwZQcpH4dER2Hy4jxbWwSB9gHK8hoZ6nYrlx4x8GI7mMH5aUh2IGYfviORdyBXXRZXxFkRfmDrDjRHut0MkbM8WKzlrj4mxOrOetoOa4O4jiGYANb3olqHWgzPqQCTQbS63HsxQc5j3Mmjitj3xataRpd9DpS5bC1n7zCuMbHNMb5ZDYB3y7amvuuNiYHyNkdHK0Pa4W8+GN499ig6poa15Bc4jqNLW1hyEaHL1HP3WD46caOoVbKWabDoQg5bpTinMbGGh7Rla9vhyjzPP3Wp8Je1kTHND3XlLjQ03RkzqIDzRFZfJbZ2kxfLyPaH5QM5GkY33G3mUHCdlOrAAeYG3qsR6Alc/5bvGiTFVByuzZ00JOwvkuO6N5YBGwFg1dIBdep5eiDRlBOm6cqBNLaY2NbeZ7+V0AFi4GxneNt90GoE2RWnJCOmqyDXVrqfIofRBro1oss7iA06jl5K1fNTY0gzjANgnKOpWQ7wPprXMZlGYkbjqPJYAEkAUSdrPNGucGNa4knzP+9EGyQwud+7zNAG51J9aWFaaO16JQqyRfNTW7/ggoGlXSzAoAWD/JQeMHqq3JqHZ6Aum7oJRzHMQ3+Sz7gQuI7/MSNSza+nms2d02Etkw7C92jHP+pvX35KSNibTQwtd+I3eqDWXMzDIzLyN6krEVegsHkeSzObmQRzQNc1p0sdeiDEaEcqWbY3m8guzstkQLmZ3PDGjZ3P2WbWNaf3sj3nLnyBpoDqSgwbEAQ3uJpXGsrWaErc6COWN0rsFld9DSXnMyt/CPtZW2M4HDxxuiM0khsvmkdVH/AAt8trKxfNiO7ZleXsPiGXSv9UEkYXAPMkbMjcrRW46VyWk93+PMT1J29EeHvc4vOVztzep9VrLr8LhogyL6rJQbehPLyKhLCczCa5hTM7MA6qqtt1iPDeUadEGT320cze6ZszmknWljZ7u20K3HkqTmaHV9O+nJBQfFeyyHhN3YOqyERcAGAv7zRrQRZPkt8WFDXkyvkw5Aoh8ea3flH8yg0R24lrB4jyK2xOe4ta1ha4/icKaR1vouU2JrWP72NkhdoXluw6DoFtZRFE2BtfJBobDMX/vJMuugZzWicjCY2KY0Wg04vbmocyAue/YUuLxBmbClw3GxRXouFYqTAdr+C497vDK1kb8xojLcbgfOsp9KX2EiiR0NL4M7NL2ejec4khnD2BxskPbRcT/mYF9t4VjRxLguCxt2Z8Ox5rrVH9QhrlpSIiCIiAiiIMAinmqgKqaoEFRE5oKqsVUFQIEUFRE9EFCKKqgiIgK7oiCpzUS0FRRUa7aoCq1yyRwf28jIv87w3+K6zE9quBYTSbicTjr4YgXn9EHbKrxMXxFjd3hHDnvaLyEvy+hrp5LpYO3XEpMPNB8yynaGS80gPOjyB/Tkg+mzTRYaPvMTNHCz80jg0fqvLdq+1/DoOzmPh4bixPjZGiBndg03MaJzbbWvBcSmxPEsaZHYqWRrtAZTmJ676LrsbEYMDMXSSPoc3CmknoEGmRz+HwSyZcriGsBq8rTpaw4icQcO4B3ed4R+5a28o/zdT0XaRPbjMEMXGwvhliLJwGE908bV1N1t1XBLnEh7HOlYdDG1viHW0V1cHAcdimGTEOMMAtwD3a+tLnwdl8LPbGYmTETVbYMPES53UXttquzwuBlmwr3RQMYHDK58ji97TyLT+ErlScLliDG8YlldFK9jIcSyQsbE4miXdf4Ijix8F4RhZzhP2UYsQGZ2z8TnDAByIYPqvy1W/F48Q4fE4SOXDMw4Y4N/Z2HtpcRs555crXPbwnBvwWJifEyfup+5imf43VepBPLpSjRE+c4Quy4PP3Ud6Ma0DS/e9VR4/DvfieGRNkkifcojud1aDYN6ALvcF32JwnymPnkfhGC2QRuAY07WPPr1XnOG8F4nxPHMwOCwp70ynLJMcjG0dyTp5r28nAX4DEd0+XvS1ueRwblF7kn13r0UHleMcFfw0mXCvEmHLbfTj4Dz9lwcNjC19l1OrQr6JFh4nQmPERZ4ZNDEPPbU8l5DtB2bfw4d/hCx0TRmkaJAXMs6UNyNteSDTBiXd2xscj45c31NdRojZe14Li3ywDANlzQAiUxsABc5uumlVvfVfOMPiXNcCN16Lg+P7oZfztLcwNFrToaPI6oPSySNxvBW4nFSVF801th1CHwuoN9SQj4XHH4fExSZWviDY35g14cxoF6chev6rGMOnwEGBdFlMVyzuaLpxoM9qH6rk4fusdFHiY2mGWF/hGQhuvhcXAbF1g6aeFFcPG4duDx8UjYJISGtkxADaLn6g6bato/crzfHocNh8Q4YMzS4HEv7zCS4hlOA0tjnbEg+69w+RuKaXY9rIu7YMPIXA5SA4gPPWgNOY1XU4nBuxuBlbLjDDH4nMZ/bBrWeEOFm8p0vy15IPEPHy+Ic1wdkH0+YXLwMwilMTx+6P1A6Zh/v9VpxeDmZhBNI8Pfh5TFiO7dYjJ1DvIE2NeYWmJ/7waE2djzCI9twvH4vDysgfiWSQSyZf32l1qN+oXYcRY+WNuLjmwUEgny/JtGdhLvrNAeFp3IGl6iivH4Obxdw+QNcCHRh+x6a8jS7AYkywPjxGJDRGbNDxAj6aO+v2VVxO0mFjkw+d/e4fF96XvbI4d27S6J3z9CdwvNMDbaJdtwSV6vGYiDEYYPAjxUkjCwx4kbNcKNOHMbjajqF5hzBBiHwOY7908gxyan0KiMpDnc3uRQIFt21/qsXPDmFpzZQbF6ELId4HZY4yC8aEG9PVHAkmRwDQ3Qkn6j1QbHTF8TIRbMhuJubws8/XzW9uIjyiAtdiI5Bq1n4nnTbqpgOD4zi8v8AwGDxmLLvxQQOeCfYV+q9tw74X9tp4mvn4fhsBHVh+LxLYyw/mLW25B4CTCODzQkMTBkfI9urXDcOrouK6I56Bzr7XgfgjnLpsT2ofLN9Uw4dh7zdfE4gLu+FfC/sSYQ+PAYzHvYcrXY3GGIyEcgxoFoPgEMcbPFLiGwyA+EHdcpoiniEUGBkc558eJa18j/PWq9l+mOGcE4Pg4xFgOzHDuHSgXFBJgg55/xOLgaHqV3EEvFoo/3gdh5DbWtw74xBB/iNanz0RX5iwXZ3iRgD5eCcZxLK8Jw2Df4hyBJGg9NVtm7L9r8Th2Mj7K8Ujw7G+FseCeBl89NfU6r9JN/arWHvsWMVM4f+pixRjZF/ykLjiDHNI+ZxMmOkP99DOY2s9Wmy5B+a5OxHarIZG9luMCMjlg3riz9meLYUd3iuC8Sjf+f5V+VntWq/TjPnoQ50mMm4gXHSaKcQ5T0yu1J9NFjHi8dBmOKxU+IB/s3YMZjGP8QcQQf0QflSaBuGYxskpjkP1Me0sr77+iwdEWcxl5Hmv1JiWz4lpPHhB8sdIzio24psl/nAByFeaxfw47NcWmkZL2cm4fIP7zBSHDl3+NrHktePZB+fC0aH9VP8tr6lxT4KYtszz2b43hsUWnTCY9vcy3+XOLZ7ml8+43wLi/ZzE9xx3h2IwMhNNMzKY/za4eFw9CiOqeLIF7b+ayc5zjZNlVjaaCCDfNXL0QYC6pZDXRTLqsuYA0Hmg2MYZAQzUjVcuCIsaycYi/EQ2N3hboObuevIbrjQmKSQsljc+Jv1ZX5T91HSN0DWZSNGgm8oQbnPZG1zNHSuNuedx5AclpOQbXZ5DkocrgAAdNz1RrCXU1ws9TSDJjXmUNjBceVCytrGgSAyAsZertyfIDmo0vAMbLBduQ6gQuRDDiBCXQRxDJRfLIacCdmt8uaB3UOInZHgS4SPcGNDNS089OfroFyD32Gilge8zMbIHPeaAcRt6j9Fsc+HCxloc10h8JyMEbnA6nNWuvToFw3lzYyY3NGY/QT4gOiBLjHTPBmAMlZQ8j6R0C0OLc+jzryqvdYukc4eID3Gywy+EG7rdBkS4O5e53UvMCCwelbIDqM2hH4TzW5kEkzXPjAaG6lxOnog1Na0gW72tZBuR2V8h1OlagrYI2zBxrM5pyuMY0aeQtdzBwaGOS+ImCd8YbUUMbgDY3cdKrpuTug6qLBvbKWSQylrW2e5bmcByLujVyosA/uf/UujaT/YvjFgdbP4j+gXYsjgbM2MEQMu3huw8/M+trRiJ4XnKxmVoO51J8z1QYmKDCwNlEETHPGUBm1fmPOytT8Q0xxtY0AMbQN3ubtYTz5pjrfIA9Nloc0nVoLSEG0SODqA0Cza4Z9NzyXHaS4DXxD9Vsac2+nmg5AcMtVusHeKIg9fujHEAWjfxC0VODCSSHHYSOLP3kRYGt1pw8bdOoylfTPhpxNuL7Mvwea3YOU5fON+o/W18twmMPD+NMnaHW0hzadQuxr6r3/YThruF9q8XGcVCWzQPcyCNwc5zMwcHGtGgXoDqegVH0LmqiigqiIiCKWiDBVYqqKqc1FURURFQVUTYoKqp/FVAVUVUDmioBJ0FrB8scZAlljjLjlAe8Cz09UGaLhz8W4Zhb+Y4jho/LvAT9gutxHbXgUF5cTLOekUR/mqO+VXkJfiFhnPDMFw6R5OgdNIGj7BdBxHtvxjESuEMrcGy/C2FtOFdXHUoPp5aQ23eEdXGguqx3abg/DyWz4+N7x/dw+N36aL5PiOIYrFF3zGImkD3Z3BzyQXdaXGJobgdAEHv8b8Ro2W3h2BBPJ+Idf6D+q6DFdtOOY05XY10MZ3ZA0MH33XnswHnY1WPej8IRXIfNLI8meV8jrPikcXOP3WVC2kHQfV5HzXEdiHObeUUP0QSyksDdQL06316oOQ+aJkL2uuUnYRmiVhCC57XNYcobqwGgD/ADWMeGe4eEB7h+J22+3+q7GBzcHI8zQuIrMCw5gfI9EGqPCThjY3NheHnwNcwmv1WOJ4bJjMPOwSlrA0G2xgNGtXfILtcIGYlzO6lYWztIaWmyK3bfI+SzxEYeDC0PdExzTLlNlx/IB5b9UR4jDYjE8NL2ZX99A6w0u8Dmc9Od9Qu74Jg5ce3vo4csLngR+IuzE6kWd6XKx+BEU0bpI2lgcCwjxajUj05LuMG8Rz4ODDDI0EzOazlYoUOXog5UeD7nBMFOdb6aQdj0pcjEYBk+Cyu8Uj393brIbpZPr/AFXIfDiJn/Jk5cRhqlcGCgy+nU1zW/EQsfJHGJbwuGI+YeTTWu3yj+JVHm58HiuzONibJc2EkDy17gM0Rc3fLy1GnWyuvmH/AOnYcxgg5mtp27i4ZgT5b6r2D4I+Ix4bBRxAx4lr5p3Suq2A7k7j16Ly3EeGYjhmGixTG9/wJr/3MryQ6EXYDr/CbJ16IMsG93D8Iwsc4TvlzBlb1p7Ltvm8/D34h2UulNOL9S4u3+wC6bFta3F4jEEUQGPjA1a9pABkB5NI1B9Fy5Htkfh8RbXNcSHRDbWta6GgPMoOU6LuxPHI7O+Juezu+xp6ABcrDYbD47A/J49gZhpm5nOyjM4db5LjQzAux87hmicCwkmqbVD7mgCuSWeKMSvGTDQMMjhsXu1APoBdIrwnajspiOB49zoWukw0hJicDeYDkPMDddPhsSY5A4H6V9ljGB7RYM8N4gxniAZHiHDWF5uqrX1PmvmPavsljOy3F5MNKC5rT4JAcwcORv8AkojtOz/Ey6R8bxq8Czr+YEg1rWi7zhmILMQ5r35WNcXtDhmDml9i63ANjyXzrDYl0c7X2QQdeq9VhOJRTMw0sgzOjBjNnU2bBPp/BFeh4VjZIBJJHM14bK98bDuWOLhdc+em45LTw6RjuHQYSbCiUuhkyMyA2zKTfnoD56LrMTi2MxcksBED3NDzG85mO38VjbfbVaHcTxeHmaWNfGWDMyiCW/bl/VBy+I4A4uD56GePFyswuV8EhyPxEG5YXgU7KNRm1Nb6Lx0uGlw4jka2R0L2HL3jaPQ7bgL0uDxWIxEDsFgBJNK54eIGRGQOkHJwF6cvRd5H8Me03EMUMRgeGy8GhnIc9uPkEMMLjo4NBJdR3FDbREfPWOEjaa4sc0fUdgVyY8YwM8cjmPIpzrAa7zPmvrUPwU4dgJIpu0XHHzRzOAEeCgy27p3juXnS9Xw34c9muFvbiODcEw/EHgnNiMY7vyw/4Q+g72CLHwvg/COJceaYeDcPxvEcQzQNghJjYPN21+69dhPg52h4uyOXiUuCwMmoc2V5klaDsC2O7N+a+3DBY97YxDi2QMjb/wCkczwHpYZQaPLVcKKXAYqOXEYesTiPFE6TDSmIzOb/AHYaNtdLr3QfOeF/Brs9h55cHxzjmLxGIYA9+GYBhWVyNm3H9F7Hg3Yfs/whz2cP7IxxkeFuJljOKdJ/lLzTRz1AC76HHT4jBMweH4ecBixHZZNDcWGdX43H668t1lJhJ8Uz5fHYpgiygSS4Zz45ZHDnf4Qegvog0vxE2Bwnd8QxOAjw5eI25nGKNtmgC0ABzj5aKTR4fgeGzPxmNa10jWuYQ10jiToBQtrf4dVzI4TG9wePmxsHYlwe1o8gRQ9QLWGEgwmAle/C4ZkUrgWl7TqQeVoNBZCSx/BuHRzO7zxuae7Y3q/xaPcPLVbZJ+IYp7XQtbGIneNuKaA+VtfTGQSWm61OnktjpAIzReHHmTYHktUhdbO6e2iKc54r3QYPdjsQ1kk8rcG2JxPciMyifTZ7j0P5VpGHhkkZNiZz80wEROhHdxtzcnR7OPqt3eTjECKOMOjq87ZKa3pvzR2IxJa6R8UhyaEUHeqDS/h0Mz4psfI/FY3DuJgloNEBIo5Wt0P/ADWjsBE+SF87mY3FRWYsRO8tfFYo5K0H2KokhEuQMInc3RrTl0Pl/NU5Y4SGS5nOOpe3c9BXLzQYuwEBmjklglxWKYD3eMe7O+K98pGgHqFi7AYXFuij4jLPxCaN/ewySylhYetNoEeRsLYXvw7bNl5+p0RzCulblZDFNZeeSy+i5jxqPKkGDuGjO2YY6d0rAQIWNbHDLe3eNGprkQdFoxPD8ZK9jpYMHLhGgmSK3yzNdyMegFdRuuewNa67c2QbNI8LSrGZSA57Wgfhp+pPX0QdM1obiWN4fw6RkkzdZX4F3dT1+F5Oof0rUjqpNhWDDSQcUxEWJwUpy9ziMNmgB/I8GwCOTl3MmKixTHwTvc9jhT2OJ0A/h6rhzYVrf30WMxs3dtIOFdOO7laeRBF30N+RQfLe0/wl4Zxsy4zsZPFgsYw5X8Pc7/hyR/7b92ehseYXyDH4LG8J4jNw/iuGkweNw7sssErcrmn+Y8xoV+ppOKYSVzoMFE9s0LW96zEYYsztO1OA3HIg+q6LtD2TwnbDhr8P2jjODnwwyYPGsLZH4YbjX8bHfkPnVFB+bib5LAkuJbHbjzoLtO0XAMf2Y4rLwvijWjEMNtLR4ZYz9MjDzaR9joutDctkk5jueqIpc5xBfRIHpaoc7WwPRY269U1u6pBsBzn/AGAtgja57WRyZ3HYZaWpoDxQAvzNWuwihxIwoIlhZhc4DnNpzy4dPRBIosPK9kZwGIliJBe95LXyUfEB+UcltkljZlbhcOcJHnLg2NxN66b9NrUxWNEtMjaWNaKDs5Lq5Wea4csz8oGfMANAOSDe/HSEFrmje/E2691xs9m2karAPc5t5vudVmyFrnVnA5nlSBmP4iQDotrYWtGZzwL1AIKscOY5nvbGzk5/4/ID+a5TOH414inxEAdHNXdMD7cQTQI6AoNDIZZA1mWeRzr/AHbQAdOevILm4fhMQnja+WfvBr3UJDiHEaWevouxdgIcA5+FhwUnzT6Z+9NloPnellXH4/EDEuyCONwI+lzdPcIrORrcPh4W9zLBEyw1pdet9eZ81oxE0bJJckmRzr1AzHXqeZ81w8Ri5pHNaZO9LWho12HQLjyTuZKX5yx400GyI3yztysjaDZ3J6rAyjCTuylkjgKzbhcN+JdQYTmA2tay4A5m80G0yhxIPM6LYXscymAtcDzN2uMX0QBsqHAjM37IN42LwQBzHNZ5rs3XVaWusevVZtJGla8rQb2u8Iv7rMHxb7rSLZV7HVZA2UVxsfFb2nQAXuLXrPhtiWwdqsOCQRiYXwlw/MRf8QvMY5hdCHDcG9F2PZuZ2E4pgcSMzcuKY52Y67j9EH3JFlIKlcPMrFARFEFURERrRFaQFVEQZIoqEBFU9UBYTzwYVgfipmRNO2d1X6Dmu4wHA5MSQcZJJhYyaDWMuV56AHQfqQvRcN4FhOGOJwuHjbK5vjxMgzynyDjr/DyClWPDtZj54u8wPB8diI+UjmCFh93kfwWx/Ae12IhEmGh4Pg2E1mmxLpXD7NpfRGQMbmJN62G0D9ybJPqtjI2hhFvcHfVmeTaEfLMd8Oe1+OIixXajh7IHjxCKKRoI6Gh/NcT/AMksW+SsT2mg11a8YYkOP/M79V9g7uPKPA0gbCtArlaDeVt+gUV8gZ8CiSWydpMkg2AwQIP/AOVrQ74HYwxOdH2iwxc01lfhHj+BK+zZW0Rlbrv4UyMoAMZl6AaIPh8vwP40xrTFxjhshduDFK0j9CuFiPg92pbM6OMcOxL9CHR4wNLhz0cN1997tl2AQBsGuIA9gmU2fGSPyuAI/qqj804j4adr4IXvPAMU9rDR7rK/30K8/jeDcU4e4x8R4Xi8ORrckLm/awv1kcPUYaGRF13bbj/ULYXygtbc4Y0bhwe39bKD8cmSMtdrzo66qFoAaMxynUHZfq/ifZns9xqYycV4Rw3GSNBGeXD927/rbS8zjPg52PxWGecNw3F4UvNtfgcWZAP+V12PJUfnbuznLJMza5kLl4eDUua8aDUc19Xx3wLiDGjhXal8bna5eI4Wva2rqZfgx2wgY9mFl4Pjo9iGzljvTUaIPGwVHhywR0CKznUArn4VzT4s7WRs+p+W7PQDqufiOwXbThkdv7MY4BrrJwrmzjbkAbXVyNxPDQW8S4fi8P8A4JcM9nvdbhWo5TeCYbiL5Jp5GwPmcSHREhzXDnQ3KkOH4lgmu4gO7x0GJJY5lCOTNs2UcvWlqw/EomYOWNmLjZK6MtjzDK72865rsW8VjxTIYGYyEZRZc0fQK0HuorpZsRh4GYOHHmbDzYeciaCduR7Wu1BbyI812HDpC6XE8QcBniBoM2cOX2/Vds7iUHEcNHBOYJmOLGOEsbSXN3e70JoA7+i6ybgUX7Vlw3Z7Hx4aJzS9kWIBdERzGbca6C7pEd3weWHE4v53M4CRrGuBP1Vrr1F0tDXDEYfiTMOS6Nsj2sYRq5x+p3mb0HkumwWKx/Bm9/PhM8AsNxMDw8skApoe3kCb1V4bxbBHvjFxCNmdwe05gSyU7g/chFegw7m4yPhpjjBZ3r4pwD/aW0EN/wAopdrD8tjeCxsdC2TCNa6TFAnLnYDlyj10ry9V5CCdrOFmPMYpmEvYBs5oOtdTuuwOLGL4WYcO6bMJWGcMhJD2l1nQDXYbIPP8T4VP2bwzJ+/D+DcUiDIZHsIdhsxBLHV0sHofVaWy93ipIi6KRgZ3Zcx1gjbT21HqvaN+fx0mEl/ZGMx0D2Ow2OwzcI8tey7Hpemu4IXVyfDXtU/G3wThGIfgJXd4xuLa2OSA7FjyavyPNEdSwvjdLw/vGU9jW97emlFv61a5Bx0z+H4uDRkkjwAHOpwe3b15hehw3wo7XTyM72Dh+FouDzNiwT7htrm4f4R4/EFxx/aDh8LwTmbCx0pLtt9NUV4c418bHOjJY+NwLaP0kHXVejj4zwrtFwUcG7TQMdGJgY53DWI9b3/VeswPwl7PzZjicbxTF4kNBfC0CDXz0JF9SV3uD+GvZnDkPZ2ejdiWEUeIzukvzGtH1pB+cu0vZfFdn+LfLSmGV0z7wxw7y/vmXoQN12/Z74d9rOMRiWLgsmHw5P8AbY53y7dN6vxH2C/TMeCZBhR3T8Nw4YcEubBE3I0cwT+ui4uLODwmTHPxGMf8xK0XE/NZdsa3DepCD5hwr4MRywsn4t2lvJoW4GIFoPNud/P2XpuCfD7sbh8sUfCMRjJ2E+PiGeRxrnlGVgb57L1VskjEvAuH4USNkGeWRndNDSfGQebuhrVcnExYvGxQj56Th4ilEjm4eTOZAPwuJ0o+SDhcLwGKw+FOEwnD8NwNosROwzo6A5ENbqfME6dVqxMuFY84TjWMOIIYJXZ2GOKg6uX4r5Wuxm4ZhcTLHLjs+ImisRyONd2HbhtVvS5EbGwMGFwwjigGrYwKAv8An5oOtw+MyTv+U4W92GeB3eIY2+/Juwc2wHnva2Rw8WE0p+YwZikd4Gujt0DK+no83euy5EkgfFeIYWtaaNgt9hXJYHJK8Sd5I1pGgHisf0UHGj4bw6G+6biWxmUve18zi1zzvYP8NguY9wMueIxxCqJyC/SxusGmdzHAtL4QN2nNmHQA6rUHwYhoMX7trNCY9Pajz81Rk6SZ2ePLIY28x4gfILj9/FKwsaBGBqcpLa9zutrmSOeO5layNo17zdvoRuoXYnxM7t3y7d3WHAfzJ80GmU4dzA4glrBq0POv2UMscrRKYi5rNBlBAI8wNwFkJTEwvbh3wsiP1NiIH6b+qjpp/BPHFiHGXUFoonpoghlgEgknMjM/4LrXqf6LWGRCN7RO/M7xNeQAK5ey3Z5s/cCOTu+bmssD762tZfNIO9mhcTEfASy/sg0PFQhscwMoPjMjaaPQDooQ8SNEE8Q01cWubr1pZyPY3/iJcPq/TO+H+PW1x3GAN7gRuje45wWuIJ+/kg29663QNhe9jPrIFg/4syxbHkBkbMAXCxFJqGjrY5+SlscWCKeSOFg1A8Zv16+qxa2R8zgx0ZiB1JdTj5Uef6IHfPgY2WVkkR/C4j9bC2R4oytEkhEsf4GnZx/N1tau/n8bH97C0fVKW+Fp5VyWuSVmKoMphGuaICwPPqg3tMUkpLZJogN78bT5dVmHTvmLGhsjRqXRnUDpRXEkLnFkWGlY/kBKcp9SdlqklOHAZKxzddXb5j5Ug7FuNE3ha/wR7t6eq2txBe8OcWu7vUaArrBOwj99llzbj8nl6rOOWGOLK7DsZvsT7G0HYYiUYqIB+MkgdF9EkThbSdNjofRdXNhDi8OcBi+KOxGNiZT8XDGInuB1DsuoIvcHn6rkx4nIAGRsY4C3BrNidgtONwsPEomxY7CtlEZzNJJZ4hrdtIO4Sjz/AGq7K4Dtbw1mAxc9SQE/LYsNHe4V/MEc2nm3YjUar8/8a4TiuAcaxPCOKR5MZhJCx9bOG4cOrSKIPQr9QEYV8seJOBj7+PbxASi9DThoT6rxPxL7IntLwSbH8OiY3ifDoz3bWN8WKhbq5nmQLc33CnQ+DkaVdUq0HMKsnlQtMzQLa5rwfpdW/spbjRY+hzA0Nqo5EDjIWtmwsZjHiJmtub331R72N0a/KOTW65R0vmtT3ukOZ7y4jTU2sM1igK6oMnPB/s8wb581DbXWaJUDTdNXIgw7pPojzhtkucaZp5oNbXGQ/SXHnQXYNglijvCtw5e8U4l/9mNqzHmfRWNsjpREMGO7ewHLE4NLx/iN6X58tluAiwcT3sw+Hc97qj7snJHW5A/Sz0QX5RrGEfKNsjK+Q2cp/K29z1dS5ed2Cyyz53zaOs0coAoD2XWS46WeXxuca/Fey4rpHF58N5dTe59UHPdin5czZqzGwXbriumj1svPntquM+d0rreRawL2k76oOR32VwIJB3sFa3yF5Jc4kncndabJdvsqTmGprog25iG0Tz36KZqBDv0WGwFqk+E1qgzugbFgrNriAa1HVahqCOayB0se6Dc3Vt89ws2u0/3otYu9NLWQFi+aDaHHY8lnd9NOi1tN11C2AChaK5UMJnjLRXuvp3wn+GMk4HHu0+FDMJE/NgcM/QzuB/tHD8g5D8R8l824a5veFrj4CKcegtfq2GdvyOGZCKjZBG2MbeHKK9qWdq46XtFgAR87E0BwNSgc+hXnl7DGETRujJBDwQQvIEFpLTuDRTxNFOaItMiInJBrCqgRFW0UVRFVWPNVBkNTQBJOwC9DwjhroHGXMzv25aJ1EZO/qQP1K6vhkUb5w6XU2MrfTUlejhc2GAMZVA7dSdyfNRcdlHlBaRZIBAcdTRPVbWu3XDbI0Hc3dUt7JLeQB7oreAMu/wCqzvQarSwnKR9gsgfBtzUG2xpSvNa830/osgQXH7KjK9L66KrC/DVnQq34r36hBl/BUcufVYg9PshPI6FEZA3z1PIpftyUurv2V6Df1QWydDqOYOoWp2HiezLlLQTfgcW/wWzrWhJ2Kb8vT1QYPikc4ViHFvNkjA6+mvJan4dzsSZDDh3gABpBc1x63yXJvW9dd1LGXf6Sg4jIcucHCzQts5RDPYIGxA5X0R2JPygfJJj4gPFkezO4HpVUfRc3n/mQOoDUitCqOqxWHwMzRLP8s90ehdPgWvs+elhcefhXCmuzyYfhNyENDZME1rS49CBYtd7mNVm1G5vkm5o1R91B5xvZ7gjMUA3hnA3OkvI12HDX1z8jSN7NcIjeWDhPB3PcLaWx5HADy1uv1XoXMjeLcxhI01YLUOHgDsxgi1H5B9kHURcFw8BLYOG8OilGpliY0tPQltWsv2ThXvJ/Z/DY52uFSsw8bwT5gNse+q7AcPwjZXPbho2yOAaXNsFwG19QNUZhMG2QyR4aJpkOZzw0gvO1nz0VHFZhBNUkc2FjynXuWB7HD9KQ4gCM4iLiFOjaXf8ADRZmvrowa37rktwOCbIAzCQigSA1lAa66barewd2aiqNo2aBQA9kHWPxQ+XM8U2Plkc1uaCFupv/AAu0b1OqSws/tIMFi5ZHvHeVKWAjmST06DddqHO8TTm39VgKMbgK0105IOBJgpJHxuw2Dw8TmygyOncczm1yy8/VbJMLiJHwytfhsO5jre1sGfO0jYO056rmbkEVdfdY5riOYUPPZBxpcG6TERTvxuIzsYWZGUGEE71181BgMPHi5J294ZZA0Pc6Q+IDQCv6LkvogEEiuhUfdNdo6hyGqDjMwOCic9ow7criXFjrIN6nQrdG2HDud3TI4nONHKALHqq9zqBLXWNx1HVR7yynuBBA8RLduhQY94W7uG9FYZxrCctk0W/zWReRJnZHZO5DFHOcx2XK/KdKLb9kGAdG5hY0eLydrpvajw17WZJCK3za2FDIA7u3OAdycW0fI2sS6F0dUxoBzHIcpHmgHvfGGFjmDUAO1PlRWmTK9zH4qEguFN3jcfWv4LZUL3Ate9rWjYEEe/WliWvERMzWTNBvI0Zvcj+QUGsxve8vZLGWHUB5p58r291XSSzx/wDERPETfxPbQHkD/NUxRvkDpRJGTRMbdB7g/wAFi1s5cT9UdGnNeLf5AKiEMe0CBwhy/isvaPKupWBZM6TJGWvYNM7nUfSle+gliuSMMiaaPg7sX0tRzDLl+WeyOMeHx6hp6A8/dBrbI6SbI5z4g3675Do3qsAydzpAMRESD4C6xfr/AKI+eGUfLvqMxmw0HKWdT6n9VJWMORrJZ42jQ2A/3J6lBrc4mIO+ZAmv6RGb9LJ91SD3rcszCwjxAAj7noVk+V0cwexgxBeKzNhBd6LS9sEeeGWAQyP1FPLT5eX2QbGumke9rsuRux7wUTyoLWJsTK1xfFM0N0vKDr+X060sHQtkyCCWRuTR2gcAOp57o9khnDYZYstXQBYWjY76X7oNT5IpQYqbEWm3ZPCWeo6rGS3uYyCUMDRREozBg62Fm/EFgOGdGaA1bIzNQ/MTz9VpeYRG2PDfubNgtdma7qSDugz7ydkvdQRveOrDmBvclaXzRZHNDWEnQvAyuJ6pIx8LAWyMERFukkOQk+Y/gurx/HuEYEl07m4jEO/FRBPoBr7qb5ZhN1zXvEceWKQyyn6mubd+QpX/AIiCnSvbA6t3SCmjpXVeOxvbx5a5mCDIm6gAaFx6ADUrpJsXx3iEeeXPhg7nM4RgfzKzy3fWLJ7e+xfEuGREvxeIc934iw5QfUrq5+2nD2vIwsBmd7vr+QXjHYJmZpxGKzObs2JhIPqXb/ZZCPCNcT8t3rju6Z5dfqNlO996dO+l+IeJnDvlgxu+mbxE+TRZK4v/AIg47jYgWYbFGVw+gR5Wt9XFcOPGyN8MD2RVu2JobX2WvE8SdA5gxD5HZ9bu044VzGYjjzGXNBI+TmGTM39FyOD9s8dg5u74i3upI3WWu0Leho7+q6Z2O/4uFkQD45BZeD9K5eLY3H4apmtkxEHjhc4Xt+E9QnHC68r8QuzkHD+IjiXCoGt4ZxOQvGXX5eXd0fk38TT6jkvGkUKFUNl9aZCzj3A8bwYSNaMVGTBmP9jIDbQelO09CvlEkMsT3smYWSRuLHtP4XA0R91rx1NYefRZCyQOfmsWnXTlqs2mN5LX96Xf4NP4rSM44J3xukZE57Gi3kch1W4mAxw5WSCRhzG320dKH8SuN4mmnl17mysHyOcbBonekHMmxefNVh7zme4nV3qtD53vcA4mgKAXHzGjZs9UBO96oM+8JGX6R5KZjdWpvqlXugyLiHbBL1pYjQK3oOqDLNyIG9od9Oag1I1rzKWUGV0a3WQF3X2VhikneWQRPlPRjbXY4bs/xKYWYBEP/uuq/ZBwGAuFDdZiN9Xppuu7ZwPDQAHF4y3c2xj+q3Xw3DD93hg53JzyTaDo44ZJHDuwX+gJpcyPheLcT+5IrcnSlzn8ZLG5WBrR0bouK7iMshour0RW0cMLReInYK5M1Kdxho9mlxPNxXH+Ye7VxtVrzVee6DlMxHcgiNrQDyrdfUPhn204jjZpeD41vzhjiD8PJI+u6YDTmnm4bUOS+TX1Xpvh5jBgu3vDXONMme6F3o5pH8aU3B9/lILdOZ5rzmOZ3eNkA2d4h7rvJXEN29/9OS6biOuJ9AApi64iIotIqiIiMEUVRREREVVRZjDzTYed0MbnNjYXPcBowdSVByMBLUfKw46+q7uLEDKSdadzXlsNNQOXnrquyhxDQ12ayHDMOgRXom4i8+XWnDQLkiaqdY6dV59uNdnaa8JFE8lyYcTbCx7qczXRB3zZAH1ehPRZNkGUjN+i6luKYWseCd6Ou62txDO+3IDtRqiuy73RviCzEhtwq11TMS0tyEusX9wt3zLfqsiwPRB2XeDY2Oayz9db5hcBs9k0bOxC2MmB+k6dEHMz3568lln06gnZcUSeeU70shIM2pym+aI5F6ktPlSysZhYNgLj95oM1DXcLMPOmU3r1QbQfCK11WWl6WOfutOcbkEUdwqHDUZtxaDbfUkZt0s1v9J103WGayDmGopUHmaPIoM/Ya7Jpe5FjVYbDY2D+itiyA7fXVBc2gPTlW6baaGimYbmiOYKhNCnURyKDLqCL6JYIvomzgQ6768kFgkVf66IKboOvY8xyRxOhd1o0o0BwLWmiNP9hCXFpNCxrogOIdl/mh0cCKo7jooSO711A11QgZQQSNRqNUFstk2NHUEbLC6vkQdzyWRvwnQ1ppuo51PN6E8iqJQJBaQAscxDdbFjfqstcxLaroeSxzDKWnpsQgEAsIaK523ksXChYNuvnoVS1uUjJp5GiPdTw5aJdtuf6KDA2WXQsHS3bJ4sgdkd4dgDqPboq2z9TmgEctb/AKLFoeTTg2v82/oghf3jPFZaDoXAj7LEgsaDFKcw0OfS+myyDnPOV0bySPEC0lYN7qqaASdiHUb9SgpdOwgNYHlw1pwI/Va8xLixrPFvmLRr6lXJ4crZwXHUOLP0r+ajw7IQ9oMQN5y7n163+iowkcAWjEwsJvwhosD3CmUXbJnZ70DgC0H1GvuqC9o/4aQP6l5Db9xofRYOLLcHw5Ds6Si3N7jT/sgkgsA4qNmII2yEuyj+JWt3dPfmEjo3mv3dWPLzC2ta8CsLKXncmQ0T5WNPZa5XsDv+JgHhFmVzKP8A1IKXYzvSwOEjAPqieCSOgafstbpo5T3MUHy2IH5IqyDnfL3WBDe5Bw03dNBtrZAZA6/Pf0Wb+/c0x4iNwYfpeHN0PWxz8kEe6Ztwd2/K4eInxtI6uI/guM35bK6CKMue7w5e8Ic4/wAguSYpGhrYMQHEnxOeMrneemgpapWzPc5ny1tAvOMrnOHrvrsg0lrY4SMPI90l2Q85r66gWFC+aJjXFrMQ66DWePJ6NI38wtQxGFzmUYcwm8rnNcWCzy9Vhlj7uR+HmkzAeCSQgtA9f6INjpYGlzJ4mxSP1c0eAt8vNa3sHcmOCUmQm3Bzc3tfILq8b2iwPDIRJj8RFiJR9AAtrfIXqV5LifbjF4xvd8MaxjpP7KJoJfJ5hrda8ysb5Z8LHt5+Is4axwxuLjAGrjE4kv8AW9h5Ly2O7dYPCuc3heHYx0n4xo01/iOgHovOS8Nx+Oyv4riflaOYmV3eSOPQRjRo9VllwGDIkEffzDT5jGODyP8AK36W+wU732vSy8T4zxmUviD5YSP7QkxR/wDW7Uj0Gq4zOHQwue/FY58z3/VHhRkb6ZjrXorj+JSNLDP3kofdG9AuBicRI9zHYWTwNFu03PQqzMS7rnnGYbANPyzIcIOrB4j77rjnGNxLHyxOMpaCSCdSqcK7EYvDYjCghxGsmTO1lcyFtMOEwspMMr8RLIbmmeKDvQcgqjr/AJzvIX+DJL+Ebj1WeFc8QvM7rLNST0XYti4XhxHmMmJkYc7XN8Av8pHMLCfGRPlEkGFigdduLReY+doOHBwrHHBt4jhoQ/M68odb5Aejenmuxhwb8WYzUUbojmezEGqHSufouPLxCeWXvHSEP2BbpS0OmcSSSSTzQdo7BcLkzywz/Ka5u6yZtf8ACei4YmEcwdegK4pm81gX3uUHLgxEeEmkYxoD45M5cBqWkVvzo0vH9smQ4/tji5sIDHJKGvxDX6Aylur2noRR9bXo5mNfiIHm7eCywfxcvvoF5vtgwxYnDYsRj/iIu5kJGocw7f76Jnsect8cuj9N7DcuqZnG3XqVCb31UrzWkQ3XqplFb7rLcK0gxrl91aG1q89lNigVop5KgOcHFo0aLK5WH4bNM9rZLizbNylz3ejf6oOITpqVuhws+I0ijNfmd4W/cr0eF7PxYZgmxzBhWDXNK7NK7pps39Vvl4zw7ANLOGYZ0knOfEHM4H+SDhYHsk6eMS43FiGL/CzX7urTzXKkw/Z7hhBbE7EyN18Ts/3GgXU47i+Jxrh38pdpWh0Hkuvcc+pOqDvsV2oeR3eCibh2ci0an+i6yXi2LkebmkF/4lw8oGoN2sbrYIN/zD3utzzfqsu8caGZx0oWbXHa4t1DRqK1CyaT6+qDe1wvULa1x2sLig8uizadUHKa6t1mHarjB2iyDzSK5Qdquw4HiDhu0PDp2mjHio3f/kF1Ik5Ll4B3/wCoYc//AHWf/wCQQfqCVzXNzNJpxsaUum4hh3ZnYgfTTWEVsReq7OKYSYVrnDcA6aXpsuHin1hZ2a08bedrCuqUS1FtlUUtEGFqqC0s9EFQKWU1QZL0XCxBPwY4XEyvhY2TvHNFDPYrxdRrsvNOcQCauuSzh4i7DYwBrmjw92QdeV5j/vks73rWPQy9lcPILwWIYy/paSaPlRXAxPA8fgaL4S8N/GzxClcNxzunMgxT2TGUEhzBYb6efNd5guNNZJ3JmMtAHPlyggjZB5R7n5XN1sHTyWyHEvY8vLvEBRbV2vYzYfCYxrnYjDwuYde9jdld7rq5OyrXyZsFimkHSpG6g9DSqR1YnpgYJra7UOI1B6LYMU0j949xcw2ABp5rKfgGPhYS+B+Vuzo/EuBkaJAS8k7a6EIOybjHt7sulaBdCunRbmYutpjo7mNgumoMZ+Zt6jcBZNlAD2loOtnqQg7+PE3Q70AWa028lubitQJKDiNK2K8+2doLjTjrd5tguQzEloOV/hrUHc+iD0DcRrrqa+obBbBOQBm8TevRdHDicwBjIDQNWuO65DMTqAD3en0nmg7hs2lsdfPVZd6BuMpvcFdW3EAEd4C0kUKK3MnIDaIdenoiuyEunhfsVkJDrThpquvEuptm2hpZtmaKJ5GkHYB/KmixYVEl1YBB3XCbIKIG413tZ9829SRe3VEczPXUEaFZZ9azGx1G64jZRYpx1GqzEmn1ahByc+9fbkVc2Uu0I01C44kzAVmcL+yybIbr+PNBvzA0Rv5Kk7EVppRWgSWMrt1S8UKOvmg35hn8Q1OotG/UQDWuxWovygWRR0rkqHeKg4AXpog2B3gIII01sKU3IdKPksWyVpdVy5BTw5dLBrkdEGZ2v6tdq1TNdeL7rEuOXWiPLkhcH0QarmqFOzEAXXMKNdbaabHRDeami/RTM0E2B7jdBAGgaMOvQqChRzusbEgfwSmgnQ+mbZQAZvqcB0IBUAsdRLS1rdyHHULE5g7Rpo7OuwFQCbsNeB51agdmaQ0nbXyVEdnaaaC+9RkN6rFzmtkIe1uc8y3UrMt0GV1u52ND9tlCZIxZt3+XxD0AQasjJG0yFj+ZGar/ANViC3vP3bnd4NO6H8FmQx31OLH3syqPspIXBtStyMH42kWPf+qDVIYmgCYOw3QNpl+yVK0EtOaOv7ICj7jp+qrc+X9zlcw7mQiz7c/ZYDuXvuIvjI3BGYA+nVBiO6eBlHcAf+23KT/yn+Ko70WYntdH+Uuok9aOlearxK5pMwbOAdhqD63qtUj4g4PldJCD+Fw8JPoeXkgxkMbXCfExdy8iu8aKIHXTwlTupGNJNYh1/wBm85Lb67HqtgdI1pPesLALaHDLf8qXVY/jPDcEHSSFrXAaiN5aL/gpu5hHOEMbWEMc8SEaAEPA/wAIJWrEFuHiD34qNjh9WdlE+QrXReK4r28kZh3ycOw57oGg8EAOPQE/UfRdHN+2uMMbI6aRjC63ul/cxV+UE+Nx86Czy3fTU+3sOK9s8Dgw6Br/AJp7hRiqw7r4enqvGY3tVxPjOKOGwsMkrG6CPDeL9fpaPNDwvh0XixzzjpBtFEDFCz//AGd7nVWbiEgh7iANghGgiiblaPspPtLPTgt4S+GR8nE8aWuk+qHDvzyV+UyHYei3x4hmFBh4bh2YNjtD3Y8TvV25XHfITqVx3unLHfKs72QatZep9FpGcGMZjZZI2Ocx7TlJeKIPX7rgOeX4abB8SBfNm8BA1tc6TCzf/uGLa3CyOFd1+OQ9SOQWbeMSsyuEcXeMFCXIM491BhDhnOw7cLjpG4eQU4PkBOX19lvEvC8GHiGA4gvGVwl+j2G+66yWd80jnyEuc42SVrJKo5jsfIO8EJ7mOTeOPRtdKXFL+aw1Q2NXaDzRFLz1UzFY52XWdv3CheyrL21tugyvkoXFZxxOm/sWulr/ANtpd/Bbf2Xj3HTAYs61ph3/ANEo4pcpmXLdwjiIF/s7Gkf/ANZ/9FxZYJ4CTNh52Abl8LgP4IK858KQdcpDguD2ngbiOzcr43B7sNKJA4a2DodfdcuItmDo2PaC4VZOy5fGsNHLgZ8NE2NvfYJoPd/S94bq73ICK+ZJXRSPWMbnRZAUFpAUOah2Rzg3yWTInyEUCL2v+QQYOIA1W3DYaTFSiOOwTtpZPsuxw/BHd3307u7jB1cRZHtyXJlx2GwMTo8Fh3RPJH7wm3X6oJw3AMwM0rcfO3DSxO8Q7u31XI8vZcmTjMGEa4cMjbGXDxPeLc71K6bFYqXGSd9K4vlaAC86Fw6FaDJY1GiDdicbNO7NJIb3sEriWb33Vu0B5IFkbqh2lUCpVq1dEWgpKmUFXfdEEVFgpR6LLVBP4LIGuaoZayEfqggKyBWTYwfNbAwIMW3S5vDz/wAfhzf98y/uFxw0Dkt8JEczH3WVwdfSig/SODc/5NodoQKDiLsevNSf+zcDtl2WHDiX4SN4cCxzQ4GzRBCuIOSN5GtMJ05rDTrbFBQkckDdAoRqtsmYJYVqlMqAB5IR1WVG0Ooq0RjSVqsq6qndBrlFwvrfKV1GIlD8TI9tAOAuhXL9F3eW7HUUvJ4jFvwuK8URliqnhu4rmFnemsdg3EOjjcxpLWPokEWQR0XNg4iWtEEszxAHAh0e99dfVdTDiYMQM0MveeQ3HqFuFggk77ClfavRwcXkiEnzB7zBuOQlr6dXLzBXa4PjZYJHB7W4SO8oDrc5m11/EleKFtNkZSdRfNbmTOMxeXAZhq1ooO8khX0LBcUjdkOCmb3RP7wyyatP++i5b8Vh8Q7/AI3DYdzDeSUUQ4jp/NfOjjC9kfdxxwFtguYKDh5+a5UHEI4mCPGtOJBOYU8tDB1Fc1Ite0n4ZweaYD5ZwLm6Ow4IbZ/gtEvZlocThsQ0itGyDMaXSQccxWGJdh4i7BssBzjoY9tVysPxeMBreEMeJCf3kc0t6cqcdgOiIuJ4DxGNxLcMyYBtF0R5ei6p0UsTx3sDoyNBmaQvUR8alZimYefDufO1od4BnBB5gjkudHxHC4qJwD2zB4JazLWb0KqR41jyKc4usc70W5szhlzgPK9P8jw6YAyYYwE6gOFFy0ydn8Dm8Mj2tcLaW2fuUHSw4gNAyEuIOt6rkNnbRDiWm9SOS5ruzp0MMxeD9LgAD72sG8DxgJDXNPXOMqDBs0ZcD3mh+5W9ssgo2CQdBa4/yOLY7K9jTRrLY0WZwk8d3G9rjrRGgQcjvcrgH5m66BbGynQteHHmSuKGYhh0Y4/mPT1UEnhILaAOtCkHNEjiHNABDTdWs2zAnU5SRsAuK0PebaHVWjau1nUwaM7HaDSxsg5eez4811unenSnB56BcWMvLgIw4dbBK3sw0721ka0cq5oNwldeUt0PRZCSmmnG/NaxhpmNzTljA06uGwC3MgiJLhKHOG5A/mgCQhuY0RzG6yzEm20PI/yUe2HD5HSSgNcaBI5+q2Nja8Zmga7CS26IMWzEGgaN7KhwANUD05LPJE45Q5gddZfNUwBo0Gvrogwz1vYN7FDJmNg+4WDgaoZtdw4LW51aNGUjkqN5dR0BI8hr7pnLXakg710WguIbZq+dLEPBq6IGwIQb7a42QD0BQkE6Gh6LUXh9Xoeo5JYIAbYPrug2mydDY9NR/VZgl7a0PqLWEeV1hxqv4rMStadHjffmoMmw1eUZOpLrv2WTYqdZeAfJq478TlJ8Ox3F0oMSHAODhryCK5ZjjJ8Qs/m0tRsUWewLPlsuIcU1pouComztsOa0crO6DkHD4VzvpHoCQkuDjmFPOcVoHG1p76iczmhp5/mRuJGphoDnZ1CDVJw2RusLgejAdP1Xm+M9o5OCW3FxTxSk5QZIyWu/y72vVjEnaV2U8uayOLic3I/94DyI0+xTex8ixXaHifFsbJhYxJCYz42OYS/XWg0aA/5iAOa65nDHeN/F8SyaRxOg/eOY3oPwg9Tqei+rY3snwnH4Vww+fAanxQUG3uS5p3814zHdjsfFI5uCkixrBsWW1x9QdB91nit10ETsLw8g8OwrI3MGVsr/AN5IB0BO3tS0T4qSZxdJIXk83Gyt+M4XxDCPczE4OaMg0bZYv1C6mZ7mGjuqy2SS9CuK+boVolmIOunqVpLwQTnFDfVBufKtBkIdbSQeoXa8L7N8Z40a4Xw2ecA055bkY31c6gvWcP8AhDjZHB3GuKwYVm/d4Vpkf6ZjQH6qUfPHPe/V7i7zJWWGgnxsvdYHDzYqT8kEZkP6L7Vw74f9mOFtt+COPkG8mNfnI9Gimhd8MVFg4O6w0TMPFybGGtH6ckqx8awHw37U48BzuHDBMds7GSiO/QalegwvwhxRIOP4zBC3myGMucPc0CveTcRNmw43zLtCuJLxN48I6czp/p6KEdLhvhX2dg/9djcbiXDl3gib9gF2WH7Gdj8E0ZODQzEbvxDnSG/OzS1TY8gi3UTrRN/bqtBxbQCGuJO1DUu/og7pmC7O4Zv7rguAY1ultwzRXut3zHD4qMPD8O0XYqJlX9v1XmnY1w0jaXEaDNoB1Fc1p+flzHLGLOh0ppPS+SD1beM5fDBCxmv4GAfwWJ41OXV3paTtZon+v3XlTi5ds9B2hcdT7VusTiub+8cR+J2ln/LySK9QeMSH++A0vxuNn/fRDxWxUri0ga5yKHr/ANl5N072g5bbWoc4blay+UOGU93rdnqUHe8T4L2d4ywjiXDcNJIde8iaGSjzttH7r5Z2n4NheB9oIMFgHSPhfFoZOZJ2vnuveNkdRujejhyI8/6Lx3xLx4w3DeGTQjvcS3EujiAGmrfpv2B8lcR8ZxMDcPjsRBA50scUrmB5G9FbsJgX4pwyNkks7Rt0Hq46LvHwsyE44x205+6iZliDjzcd3O5WuLieLGPwYdrWtIoitAtspHwNsNyYgtir8zs7vYbBcluL4dw9hGHAdIdydXffkukmxskjrc4nz6Ljl5PNB2WK4lJJK5zZTRv6G5QL6BcF0m2psedrUD0GqeuqATroUqyr5peumpQA0JQ5qhr3XladFkIDoXOr0CDAkDfRUW46NNeS2ZGN5A+ZUa/0rlqgCB/4tFe7YN3WEzEDQlTMdbKDOm34arzVrS6WsO6Dbmnug2AhZgi1qBJ3OvLzVF9UG4EcwsxRHn0WkFZg0itoOlFZj6T6G1qBW2M+IeaD9E8BLn8EwTgHf+nj6ajKFy5fE7XZdf2YjH/hrh4c0jJhmGyfLkuwloG7NnkeSziuvlY0TPoUL2WFLbKP3pWC0yxpCDSyIJU1JREpK1WVKIJXVWtVeaIINwuikgaMdMx4GjzuF31c11nFInRytxLPxDK715LPllxc2a4k3AMLiTmbmjk3EkZorSeGcVwtd1LFi2cu8FO+/Nc3D8RygNkaCK6A0uzhxMEtVJVjQVsf6Ll3jo8ycacLTcZFLhSTq57czf8AqXKhkixDQ7DTNkaNLa7RejIjkacwa4HTa9V18/Z3heLcSYBHJ1iJYfXRazy1I4DXHKWeIDoSs9ARceb1C5J7NYtsZdguId63kzFNzD0zDULS/hvFYB++4aZGjnhZRJXtoVrPLEitvvnhrxGCCMhJ26IyZrowyJkcT71e0myOhXHklbG8DEiSBx/DiGlhP3WwSF0RDSHM3BbRH3WqjnQ4rGYd0TcJiDI53iBY4jKei3x46MOkMeeHGF1mZzvCD+IZRta6oluQBhcHXqSdFkXAZmkCQvqn9PRUd7+0xGI/2g8YoGzHkkIDOu3MrsIePZj3PDYZ3uoPjYw+Fo2cLO+utryomfAwCJzHB2poX7I9+aYOEgied2NBAHoor2jOKCecyxcSbGX6vZJGQAedH+q3wdoo3zCN8RDz4Rmu/VeJbjMM+YGTDUCdQ1xBvqepXLZjuIEOjmJfE4EODXg+FQe4HFgyF8sksMjGC3ZXEkj0PJYw8ZweIYWxSNseLMPFlPuvF4fEMww+Yw2LfNMz6WvZVjnXmt7uLnFxGHExNa28xf3eRwPKiOao9scXDKB4BO8HXw6j7KNxcF+FzYjs8OZm+4Oy8T889gZHw5klk29ufMSeRvot7uKgYwtxWED5SQ1zA45nHrY3QesOOwxkc12HebNEjNXqDsAsvnZmgiN8DmjU1YND+K8oeJYuB5zuY8D63NkBoc7atLcVHGc2HxUk4b9ELmfWOho/og9eeINeQ9s5iFaAVld/S1pZxaKWTWPI8gkudGRl915NmNw7XZsJhnxYrePM85Wn/KdlsdxDFSRvbxBz24U0ZC2TMQ7lXQ+ag9I/iDsPF3kk4xAPhLWMqh1I1ta/2nh5mtzufDX0Fng9fVecgnBLjwyTESyj8L60b19VnPjJzGz9rQSUD4O82vnr/JUemw+Jd/8ASl0rSfre4WT0WPfsOLd32LmZu10QoBt6kdSPNebGIOKLX4R0MDR4CHEht9QOvVZtxsUZrE4UTSt0L3tJLq6eXRB6dmPeWnPhnMadO9yaV1vouRDi/BriHZ+Tsor7LzUM2Ocb+YgJO7TJrXStrUjkwTowAZG9AJHUfbog9YziUAJjnnYXjetB7Xut+SOQeFrtdQSLXmGcYa0thlic1w0EToiK9OS5jcViGW508Tmt1dkJzEeQQdq7CuomiP8AKcy0OjdsXA+TjS4sXFcNLTMPJGyWT6XB16+Y6LmMx8jI3PldE4N0Ijs156/wRI1FmRtF4HPeyfZb44qIMvgrkdSfbkq/HtcGuNxHWszdSPJcDEcRZHNbY+/JF5wwn2NbFBzZcVJG0ySDKxo8Va6f0XXyTwOf4ZXMb/7bTeb0PJcTv5HyB/zMURcfCyQElvkSuN+1I2NfEI42MBpzSwVfuiuxdi5I3fuBK+IDQMBcW+qCdkrRI97mucLOVddHLMW5sM1jGu1DGyU71138kE0Rt00krXuPjDKFH+qI7H5yVrSI2PLGnV2XTzNqSTtld+6kMbtgKtrv6LrDip2OoMlMbRo8NtuXqtfzOHIIwzXtdVMc6QkC/LoqO2c90cZM0rJIwdmEgg9VrOKa4BmFzd4dcrnakdb5Lp/mHs1kfE5oFOY0nVajicjcuGLYgfraSRaDvG4zKXNxFtcNQ0HWuvSkdxUYcZg53dXeYjQnmPZeffMwBvfFzjVsdE6gAtbsfK12SN5MYHhvp5qD0p4i3ExZO/MVeISN301081tl4s2NzsQXRyWAAIxlo9SOa8jJj5O77uSQMYD4RdAHqFnhMJjsYbwWHkcOcjzkYPc7+yD0x7VNeMjvBlOoLbDx6dVhJxDheOcIZ+HNxEkmzGxC/wDppcfCdmdGux+McTWseH8IHq46n2pdzho8JwyEx4LDsgDhTnt1LvVx1IWarg/+EuFuk79+BwkRcNWTYdryB5gaLnO4VwJgjEnC8HM6E2wPhbQPkNlqlx96NNk7gENC4r8Q8g2C0N3c6g32tRXby8UOlGiBoKsf6Liy8QeRYdTTsG/71XUvxkZLmteWubqcwJ/36riyY7Nq177PVua/Q80HaS4priAQQ4HcNK4r52jXvmht6EnXzrkurkxb2eGRttJ1rXN78wuNJO8v3cSRZJOpHL2VR2j8e1tmJgLhyBu/Pr6rQ/HSGg1xLRvnbY/T9F1jsQCRTCHDbLuPdZMla7xA5nHcWQb9UHMMpFkyOcXfiB8Z9TtotZksVbg3m00fYfzWimtadRlO4Bv/ALo55qhITWw6f7/VBJZsookWeXX36rU6cW3O1wzaEA7jouJPK5hLWaO5uW7hmELon4vFPNO0ZmP6qjlG6trXbaHLloIDs53iafoDDosmx3u7nZBcAL/mtzIhdnQnfkT5CtyoOM8kM1J0OgJXG+dax1Nka87ZQLvyXI4gAYssLcrnaEHQ+9LjYHhg/aMEkwJa19kV+iDtI2uAa6QOAq3MYzYdB1K8Z8WWub2Qwk2HbPGxmNbfeQZLzNIGt+q+iiMusGwfyl16dfJeK+JvDIpewmNlIzPwxbMx7vEbsCr9CmD4dLiHyNOd7iTuNgtG6pGtbqG1tlECrWl5pos+S5MeAkcRnIaDzGqDi2s2QySfSz3XYswkUIBc12bq7X7KunY0aNFdOaDiDBFtd64g/lWzu2sacrAf8QCGUOdeYeQP9VoklJJ0CDYZaI0bptutbnE2M2W+i1F7jWgB8jssS81V6INhAHU+6auvT1WsHTZLO+yDZoBdg0aqljdndYirs6K77bIMh5KjdQAAH+CDeqQZDerWQ5VSw2GqyA0QZjZZtJ6rBp11WTTog2toELdCM0rWtFkkAddVoA1XoOx/D3Y/tJhGtGkTu9cfJv8AqQivvPCMMIOFYWOtY4mjaxt1WczQ0iwdeZ5rsIcK+HDMa7wuy68yuBiQWkb1yvosq4UzRnB8lqW6WtKWFWrjO+2FealHnos66JSqMa80rRVKQSkryWSBBKWL42yxuZILa4UVnWiUg8/isI7DPyuFg/S7qFoaSz6TuvSyRMmjLJRbT9x5rpcXgJMMS9o7yH8wG3r0WdxrNWHiUjHW4natTf36hc+DisZ8MjGObYIu9D68l0oAO2oSqWI1XqYMbHI64nFtj6HDRwXLZiQ5u+3TkOvsvGCR7abmNDYLlx8SmAAe/PWwI2Ui16wuD2uY/I/qBsR6HRdfiuAYDEgujjOEmOolgOW/UDT9FwoeLuDm063DY0uwi4xE6iCQQdLAB9k4zC15/E8M4xgQXGGLHxA6vi8ElemxXE+cYxw7+DE4b/FJEQPuF7hmLjedJAL1onf3UdFFISBlN+hv2TlqR4yKRmIa44eVkg5ZHaj2WwOLZRnYCa5mj6rt8X2T4XipjL8uGSm7fG4tdfsuGezWIw7i3DY15i3AmbnIPrvSvMjiRvbnL5fGByGhKyjBMgdESwE6AlV/DOJxjeDE2dq7tx9Oq1mLFtH7zh8wHVrg5a5Ykclr4gTkaWv/AAuvYrZ8xN3Za57ZWfiYea68YljXlj2Tsd+IOhcVsgxMWphniJ/zAEexWqjnMla+OsOBE4HxG9HBZl7I9MQ1j5C3wva76elLi2X0aJcNnNWYf3RbQroSNT1VG2NvdO7yQiRo0LBYu+vULOPVxfhAyKQbuBy2OgvZaGPawkwjK6tyf0WbpnysDZifDq2uSDYcRPbo8QXAEeI1ZA5EKtEbI3uGIdIC3WNzNHpFNNE3LhyA125dQJ8j5LU0xssta8SDVpB8IPogz70St7uPDtw8g1DhYsdCtjZsRBHmcY5hdZM2aj1pajPNJDWJLnxA3qdQVGCNwLoCIXAficdUG9734p7HyluGoUSGVmHkBz81mMbiYZxHHO/uwaEhusvUhcd77a1uKD3V9ADtuqybM9oLMPmEThq1zgQeqDa50bL7meVzQbyuAt/oRss24tkkmWHCsheTbHagsPUk7rhxhgeMjyCNnP2Czca0mfbTsWHYoOzbxDHmItdK0x1TyH5gG8yApHLho254ZpnvZRbHNIKfXousZmJ+oFo3DjV+SomiGvy7GmtCNweqDt28TklBjmjdC1+jsQ+LVnStFujnljuWHHDFSN+mMx5SetefRdIMVM5hjkkzRu+oZrWAdFqWGVpH02QRfqg79+OlcxrcfFLHH9TMzqJd5HlputJxEjCTgpC2Jx+mSSnZuevNdN3jnRlrict2cps2o99huRrm6ai716oOzfiYe+f853jsQT+8Mb6+39UPEMQwkYVr3wD6LZoR5+fVdU+eNtB5iZl3L3C/dYsxIe8CF0kmXUNjs0pR2Lnl5zxzxgnUssjL5DqsTigZP3kYe/8AG5zycx69Fri4fj8QM8eDlp2tvpv/AGXJbwDijv7UYeFg5ukzH7BLg1DEyh5LZR5U6lh3zBdwN/6iPddpF2bjJHf4yZ3VsTWs+xPJc1nBOFNOsDHk7F5Jv9VORHmfmWsd/bHvPw0b/RbGR8QxcdQ4TFTNGuZzMrR7upeujZhMH/6fDxQB35YwL9wq/HxN3JPQus0pyWPMs4BxOaMZvloD+V7i4j7aLlR9lW6HF8Qldf4YmhjT/Ndw7iALfCL6Hb/ZXHkxg1u/F1rX/fRLoyw/CeHYEh0WHbm5SPdmN+vVcl+Ma0ANc3yA39F1RxDAb7yhWziKC0uxrW2GVmA1IIulB2b8a5x1AaTu113/AE91pdiC5uZ7mitCd11EnEJicuZxHrouO6VrnW9oLhoG9FR28mNIzZcpI+rXfztcGXFk1mcCRydrX2XCfMZCNBYGjhy8vRYElpp3hDtwg3SYl1AMOn5ef3WoySPJLpHG/qs7LEgUdRfksSSRba05INmYM0FWRuXXS1vlJYS7YmzpRcVgKcaGgG64+IkOXTbYDqqKwy47Fd0x3dwt+st39LXP8DG93FbWj8Na6eq0YdrMNhhGHHO7V9BQvN5iST580HIDiAKkuxqCDr5H+S1SSZWk/wCyVr7zM6huVhIbIG4CDGKEzytjJ+t1EnpzXbTuYwiJt1GK0FELhYIhrnvI+kUNP4qF3NugvQHX7IOVvqcgaNLqh7LZbowaDdNyRy61yXDZI7NpZ5bg6e6yEpa0HNoNqcdPZQbhU2KaHEZWiwFzoQ0SChYGmYH6T/NdZC8iRztaoDVc1kgd+KwPqNCj0A8gg7CJ/NrCer3eFxHod10PbiOV/Yzi3yzQZvlXlpbvXPT0tdkx7nPDrJd+cjL/AL+y5keFjmGWYEtdbXbEURV10QfldrCWBzRba0K2x4ZpIMjgByC5fF+FY3s/xnF8K4lGY8ThJCxw5EE2HN6giiCuvc93MlbZc8PjjaGtF1sKoLE4o3TCQel6LgEuq7WOYlBypJnZt79d1qMji7xH3K12d6tQ2a0QbHOHI7dAsBuL0BULTfXorRQSqP8ANUgckFDf3VAIBKDEjyVrT0VAvlsqGn2QQHKbbV+YtQClnlA1ca87VDc30Av/AMoLv4IMRdVySl2GE4FxbGmsFwrH4kn/ANvDuP8AJd9g/hd2zxgzM4FJC3riJmRn7E2pR5FZC19L4f8ABLjc2Q8R4nw/Bg/hjzTuA9gB+q7/AAfwM4c0A47jmJlN/wBzA1g/WylxXxhoJO2vQLJpBeGA29xoNGpPsv0LhPhD2LwwBxOHxmLrfv8AFOAd7Npes4ZwzgnBIwODcIwOB0oOigGY/wDMbKnIj4D2c+GXaXtBklZgXYLCu1+YxgLBXUN3K+z9kuwPDeysAOb5rE6F0pFWR5fwC9I/Fl1uLsx5uJWl0xy2W1zvy6qXdWNmIlaWkbEro8Uf3hIAIHNcvEYmmGideZP6Lq5ZAXaHbekVg4+JTzQkWnta1jGoQUpWuv6KEc1USrVIoUE52EF80ACwlDqrsml+SCK7JSoPVBFbrZCVLHMIODiuEwzHPCe4kP5RbT6j+i6vEYbE4TWeI5R+Nmrf9F6NM2u4Ui15cOa8bj1CuXVd1ieGYPEEuy9zIfxxaX6jYrrZuF4uDWJzMQ3oDld9jupFrVXirfTdQ2Bz0Wv5jI/JK10bh+F4orYJGu0sFUZx4p8el+E781y4+KSDTM6q2AFFdfVoWaLnGq72PjGdozHxDdtl1+5XIbxCJ1B7hmFg3QrnfkvM6ja/Mq946hfLqNlIterZiA8ZbzDclzdfUf1WYe17gfCb/wAN/fp6rybZ3N1BN9bXKZxCQb+InWykK9GGudq0McWn81X6LW7AYTFMzvwscoq/EAT560unZxV4cNGmtvKuQ8lvHFATmAIJN2d1OI5Z4BwmSrwwvfwvLf1BWxvZ3hjTma3EtB3yzuXHj4iH2QGknWnO1++w9AtjOIMvUZdLBFn/ALe6vY2P7MQSV8txWeF35Xsa9az2WxIHi4rHLZ0zYcCvsVvHEIxoXW0652beq2sx0bR9W/U6/bkl1HXSdm+ItfUWKwcjeWaNzSP1WP8A4f4oHfRhXuI+oSEX7Uu4bxFtagDobWwY2Mmi5oO4Nq3SY6D9i8bawl2Bw7qGzMRv5ahYv4XxgNbfCnV5zs0XohjA0WCaVGO5AH0o6K8tJjzn7P4u3K08OcWk6lszPD7c1kOFcTL9eH5Adi6dtfpsu/djQTR0HmNU+bZVB4rz/wB6py1I6L9jcUOny8Qb1M+/por+xeKZbEWF3ogyn+IC735pnKSweSfNxn6iLrUf73S6THSN4Fj3DMZ8IwdA1zv1Wbez2Mz+PF4UXzETj/Ndt8229ACRoDWqvzbGjaj1B3++yXSY6qPsxiy395xOAX+XDkX9ysx2Uc7+04nI0f8A2omg/quy+eYfpsD/ABVawdjgQSxwJ871TtemiPsthgB3+LxM3T94Gg/YLcOzfCgAJMP3juZfI43+qx/aBsgOAv8ACNL91BjXEkEh16UTv5Ijlt4RwuA5o8Bh2/4sgcfuVvHdNoxty9MoAXWfNOB0aGOrfoFrdiWud9JN6kbuSDtjO3MToOWp1ta/m2tdvr+UfyXVOxgNte0jTwkLW7Fk6ZiW/avQIO1diw7w3d7jcf6LW7E2L70FvmLPqaXUPxoGgIJ/w6V/qtZxTs1ga75ifurB2xxDA4lrzrvp/H+i0vxpZpXueXmupfPZIv8A6hZPnawMrtxd/wCLUoOydjydMxLup5+y0Oxj6pp1305+RXBMn+bXe1iTZ/mg5LsW925ynqtZlB1N5vbRazZ+rZTUbCuqDYHEggfTzCmcczfl0WIzXvytceecxUIQA4mg4i0HL7xztLQO3Gg105rRHmy292Zx5rMeZ5IM83I0sS8XoDaxJRugv7KjJxpuUV5rj2HYgCwA3XXqs3vDWku5LVFdE/iOpQcguzOvb2WBtL18lMyDNhptrAlC8LW+QNYTyRG1stQ5Abs2RSgfW2notMRtt36LZp7orIm99aWTXkuWskAhVp1vooN8bgLJBOtiiuSyQnL3htg1ytGq6/MeuqyY8iQGyHbgjQhUdrDiHHL3by69QTq7/t+q7Xh87WPt2p/Frp+q822Ym8xcS7fkSufhsSABbom9CdNeup381B2/aDsl2b7YYdreN4LNM1uWPF4d+SaMflDtiP8ACQQvnHE/gBIJXO4J2lw8kZ+iPHwOY4eWZlg+tL3zMQ9g0laQdnfSCtwx8rW0RnbWwOv6J38D5E/4F9qGuysxXCZPMYoj31aoPgV2lOj8dwhn/wA7j7aNX1358HwurXz3WbccSMu5HMG8vlaXSY+Rx/AvjAbmxPHOFReTGyPI/QarlN+BRIBHae+tcPOn/wCS+psmfdl2c9XVV+v8AqMSXWReg+nn6+ql0mPlg+BGIs32khA5XhD/AP8AS2D4FtDRfaVxf/8A0ab98y+pjEEDVrgBzNX/AKrE4sXUTbO9OCXSY+YD4FwUB/4kkzc7wYA/iuTH8D+EihLxrHuI3ysY0L6KJx9LjfWhv69UE4c2o3u0Nb2P9UukeIh+C/Z1gqWbHTH/ABTBt/YLnQ/CjslEbPD3yAf+5iXOHvqvTlxA8TiRvof96eqoLiPqDTyI5Hp5J2THWYbsV2YwdGDgeAaepizH9V28GHwmGbWHgija3T93E0D9AsCHx0XMs9Cf96qGe3i/w69A31Qczvm3ZadOhOiwM8jtGRAAmvEFxG4lu9OGvLT9P5lBiWNsgua3Y+LNZ/okVyxYBc7LZ3c4bf76qgPq8xAI/DoSPdcL9oNGluB9BofILE4zxUG+Lc0dSiOxDmNsggf5v5rB+Ia0HNttZ/lyXVvx5O7m9OvsLXHfjCPpfZ5eiDtzihdCwRyWiXGgDwn7rqnYlxFAmuix7xzjbne1qjky4jvHWd+q15ua1Bw3Jta3zAGgkHIzaq5tPNcQS+ZWYlvmtsuQSUBHMrSJFc5PNBusKg6IeiwOnNEZl2u6xMgHsuPI9w2XBxE8gBylFdm7ENaNTS0ScRgZeZ4XmMbi8QLq10OKx05JtzlB7qXtBhYxWfUea4U3azDsuja+fy4t55lcV+JcTupVj3kvbNg+lpPuuJJ20kvwMr3XiHYg9Vg7EFKsewk7ZYo/TQXGk7W40/3lLybsQVg7EOPog9NL2lxkzakmzDodVqi7R4mE6ua8dHLzLpzW61unNalB7zDdrsM6m4lroT1+oLucNxXDYoZoJmP/AMp1XyV05HMrD5hzXWxxaRzBopCvs7Z2mtVlmadv4r5Jhu1HFcGKZijK38sozf6rucJ8QXNoY3CeronfyKk0fQ9Dtul/9l5nB9tOFYkUcUInH8MoyldzBxGCdodFKyQHm1wNoOcARppSyBPIrjtxDDzC2Nkadjog3CQnc36LMTG9SfbquOJGnnqs7B2Kg3CYgg1qtrcVrRc4dCCuKK8vdVBzG4o7lzXG/wAS2jGMOjrPMggEWutJ131WTSQg7VnEXAguoN2ph1WwY+xqHEdBsPJdPmKuc1ufS1YO3/aLho12nI3/ACKnz7PxWORG+vqupLz0VzHqg7Y4tjQQ/bkOYUGNYD+UeY/3S6oOIOiuc80HbDGNA3Dwdt7/AO6HHV9Ao/iNbDzXU5z1QOKDtHYok3bQ7109lj82DZcY+mln/sutzk7uVz2dSg7D5wjoR9iPRYnFnZwZXLzXALj6pnP/AHQcw4xwNAaA2A7Ug+fVYmdxN7+R5Li5kzDqg5HekDwmtdrWOYjca9bWu7GqmbfVUbbrmpm0Wu6S75qDZeptL0u7WvUDU/coDRoHZBntsUvSlhvoVbQZXytSyTWqxzf9kMrW+qo2OOSPWrO64bCJJjIfZSWfO7u2n/MVsYQ0INw1FnZW/wBVq7wVR2KwfiWtBcSABvfIIN5csHSivJdLPxuJt+IBq4J462U1E7yLuQRHoZZhI8M5A2Vm14A/kvPt4pHC23O/VcTEdqMLFo+do8g7VFeqM46rjzY5kQ1dV6DVeKxPbSBrT3DTIeXIfdeexnHcTjJTJLMQToAw0GjySD6c7icX5kOOZK5rGuuzr5L5bDxaaJ4L5ZJB0Ll22G7UQwgWHNI50qj6SyUBoAPJZCUFeFi7Y4U/34B8xS58PabDzaMlY4+TlFes7wcyshJQXmxx+AMzPkDRzs6Lr/8Axvw98xa3EtAboCdAUHs+8B2TvQ1wJK83B2jw0urZmO9HLnwY5uIeCwggaIO4Y8hu5WYkINg36rjNeKGqzDxe6g5jcU8aE36rcMYb1Ljfn/JdcHDZZB1bFB2Zxdggk9aIFD1WQxbWgNsnoASKXV5yNtPPogea0Onkg7j5oEULcOYI2+yz+Yc4jO5mm9iwT0J6rpc5oG6KokPVB2/fsuzrR3IqisxiSdnj1cKtdOJ3dfQ9FkJiT4jaDt/m20PEB0B1/Xkr85r0A2yi/ZdR33Im/VXvqrW/5IO1GK1u7JPMnU/1QYuzrqBsboD0C6o4h2248907/m+z0rkg7V2OOWiA4bUT+oWr5oluUWRudN/Ndf3tGwShmO+x6gIOc6eR5Fka6Cxeid6KBJuuf9Fwe9dvzO/moXk6nTyQcwy5tQMoGwNX91qfM5xHi+y4/eNvUrEztaTbgRyCDkd5e+ulKgrguxsTPxajddfje1HD8ECcRi4mEcs2v2Qd9nNVSxdiGxglzgPfZeExfxAhJLcBC6Un8b/CP6rrH8cxnEH3iJSWn8DdGj2Vg95Nx7D5zHE/MebhskfEGPGjhr5rxUUxOlrmRSvBFEoa9kzEA81vY8FecwWIkcQDZXeYZsjgNCqy5rTa2tHosI4nLkMhJQbSNNVjlBGg0W3L6pvo0UFUaHQglaJMIH3oubVK1aDppeFiT8P6LqcX2aE15RR6heuyUPJMo6BB83xXY/E6mOnBdTiOzWPi3gcfRfXDEDypYnCsOmUe6LXxOXhWKj+qF/2XEkwsrTqwj2X3N+Agd9UTT7LjScEwUn14eM/8qTCvhzoXA6grU6NwX2yXsnwyQePDAX0C4cvYPhcgsROF8gVJhXxpzD0WpzSF9dm+HOAd9Ej2riSfDGB15MU4eoVhXyhwctTgV9Qk+F0h1Zim+7VwpfhfjrOSeN3skK+bOtaySvoMvwy4qCcndu9HLhS/DjjLdsOD6OSFeIJRkskDs0Ej43dWOIXqpewfGWf/AEch9Fw5Ox/FmXmwM3/QkK4WH7TcXw1BmNe9o5SDMuzg7f8AEo676GOXzBLV17+zXEW74OYf8hWh/A8azfDSj1YVIteqg+I8WnzGGmYeracuyw/xA4Y+gZiw/wCNpC+eO4Zim7wuHqFrdgZxvG77JCvrUHa3AzV3eJid6PC50fHYH1lePuviZwcg3YfssmtxEZtj5G+jipCvuTeKxO0Dh91ubxCF2gcPW18Ojx/E4voxM3ubXJZ2h4xH/fZv8zUi19sGNjP4h91mMVGR9Q+6+Lt7WcUaPE1p+63s7Z49u8IPukH2IYlp2OivzDCDRXyNvbnFN+qF33W5vb2UfVHJSQfVxO3qnft5EL5Y3t8RuyS/MLYO37a1zD2QfUO/b1V71pXzMdvot85Hstje3sNf2v6IPpXeNPNTO1fO29vICKEoWY7dwH+9ag+g5wEztXgB26g5yj7oe3cA2kCD3xeL3TvG9fuvnzu3cB/vB91rd28g5SIPo3fNG5CgnaOa+aO7fRXYLj7LiYj4hTAEYbDOeeReaH2SD6o7EMaCcwAHMlcf9pxPOWA5z1Xx89reI4qXNj53Fg2jjFNHt/VdlB2zZA0Bgdt0Vg+oxvzHPI63ea2CcAb0vl3/AI8dVAO18lg7tvI7Zr0mI+pnFsB3H3Ws4+MfjC+UydsMSR4I3uPmurxvHeLY4ZTK6GP8kWl+p3UhX1bG9psLhyWMka9/Ojo1deO0RndUbhXMlfKmNxQdYLz6m1zI8XxFgpra9lYV9Vi4tExvifr1tV/H4W/iGq+W/M8Uk3kcPQKGDHS/W+R1+aQr6Hi+1uEwzC6WdrQOQ1J9l47i/bTHcQfkwxOGw4Og3c7zJ5ei6v8AZOIebyOJ9FmzgeKcdI3k/wCUqwrQeI4l8md8z3n/ABHRchvFsXQDZS0eQW5nZ3GO/uZP+krks7LY9xsYaX/oKRK6uTFzzG5ZXu9XLUXml6JnY/iTtsLL/wBK2jsRxV22Ffr5UkK8sXnqscx8164dgOLE6YVw9Vtb8O+LHU4cgeqQeODioXL27fhtxQ7xNHutrfhjxN24YPdIV8/LisSddND1C+ij4W8RP4mJ/wCVPET/AHkY90hXzkuc76iT6ldt2d7j53EyYzDsxEUWFfIWPaDtW1817EfCfiBH9rH91ysF8MeI4Mz0+I99C6I61QPNIlePZgjwrDcVkhqWLuo5cLK4A21zxqPPkV3cXG5sJDgnCOACTDMeScTHGbN3o5wPuvQQfDviLeCTcNfPC6N9ZXG7Z4gSPQkLj474VYzGjD3iom9xC2EVZur1/VItRnaRhx+NwufK7CNzOL3BrasczpzWz/xPBHhfmH4iEsziO2TNcLIvkT0WWI+HHE5cTxGZskB+ejyEZz4NQemuy4LfhVxUcKOCL4CwziYu7yjo0itvPdIV2Le0mFEEc75wxkjqYTJ9Vb89lzIuOQm5RKHNc3OAHcrqx7rq8f8ACzF8QkY6SMRiOMRxsZihlYANAB3fvurh/hvxzDTYF7XYRzcLC6FzDKalaSSb00389lIV3LeLRtlc98lN+mr2O6yZxCJuhncJR1cT+i6CX4Z9o5cFLE7G4fvJMT37pBKRyIqq21XOl7AcdOMdi4TAJyBlEmKzRtIAF5Q0dOZpIXHcftKB7crpADzp1UUixkbASZCXWd3k6Lzcnw27UOgiEePw7Jm5u8k70nvLNjStKXNHYXtO3Fmf5rCACDIxnekgPy1n2161+qRbjuIMa1ubPIDeup2PRG4lj25pJi156OoD2XSYfsD2sEM8eJ4thpe8ZTHFzgY3XYO36LlR9geNvEbsXjcO6ZopzmSOax/m5uUn7EJEuOwdjWuZHnkog+PKa09llFjo2NcDJYJ8NmzS67DfDzjokxLsdxiCUTtygRAs7vW7Gh6Utrfh5xRs7Ht4vGGRROZG0hxOY/jcdLOu1AJC45UHEI2B3eygg677HosDxGANJmnLX+Tqy+y4cPwy4mcPPBi+0T52zNAa5zTcZBuxquQ/4VR4mWKbG8WkklYAHFjS1stc3C/4UkLjb+3cNGAyWVoeRRF16Lgz9qeHYd5GIxgbI004d5QBHKlvn+EWCxU8mIxPE8Q+Z7w/vGtyltcgLoDb7LbP8I+DYvHnE4rEzPc/V4ays5rfff0SLXT47tvw7DFhmxBaJYxJG1mbVpsXp6Fam9sosQMKyESuGKZI+N1UQGXd/wDSvRz/AAq4NJhoIe+ncIAWsMupAOtaEaLns+HXBmCF0feiSFndscXaNbzFeYJ+6RK8G7tdin418bYCMM2FsrZifrDqyj1s17FdJxXtRxscSxOHw5a2OKVzGuykmgaX15nYTgzG922Bxha0BjC4+Egk3fPfZb4uxvBmAOlwEUsp+t7r8R5mrVmFfBZZ+M44k4jFzuB5B1D9FcPwadzrLDfVfoOPs3wmP6OHQD/ltclnDMHH/Z4WFvowIXXwrC8AncRUT3ejSu8wfZnHvru8HKfMtpfXxAwfTG1vo0LMMA0RHzjDdj+JO+uJsY/xOXcYXse9us8o9AvYZfJA0XsEV02H4Dh4BoLK5rMK1jRQC5halVVlEaBGLAAWWT2Wwgb7hT2QaeW6EHdXKrVBBiNTytXfZOdJXRAqlRfPmleiooc7QY11VI81lXW1KQQAqEX6rKiqByQYFuu5VyrOtNdfRNPZBgWKZNVtr7eqULQa8umyCMei202tUsdLrkg1GMUpk0otBW7M2tGgpoeVINBjbl0b+ivdNrayt+lbfZWtNhaDjdw07tGixOFiI1iYb5loXLygJVoOCcBhnfVho3erAtbuEYB++CgP/wAQXZUByTLpsg6o8A4Y+74fhj/8YWH/AIa4O/fhuGP/AMQXchqZdUo6R3ZPgbzrwvDaf/bWs9juAONHhWG/6F3+XVXL0Vp082exHZ52p4Vh/sQsD2B7OOH/AO1RD0teny1SVZ0SpHlT8O+zR34XGP8AmKwPw47NE68Ob7OK9bloploqEePd8M+zLv8A6Ag+TytLvhb2aN1hXt/+Re2y9BR6plVI8M74Udm3bRSj/wCRaXfCLs8dR3//AFBfQMgCZdd7Cix87d8HuAnZ84HqFgfg3wI/3uIH2X0csHmrloc1SPmh+DXBTtiJ/sFP/Jng52xU32C+l5epVDVB8z/8mOEf/wAqb7BT/wAmuEg/+qmr0C+mZACqG16IPmg+DfCeeKm+wWQ+D3B+eIn/AEX0nLZulCzXbRB85b8IuDgazTH7LaPhJwQDV0x9wvoWTomTXYqkeAHwp4C07Sn3W5vwt7PirikP/Mvc5AmQV/JEjxbPhn2fb/8ATuPq9bG/Dns+wf8ApCfVy9hl0TIL/qlWPKN7A8BYRWBaT5lb2di+CR7YCOvML0tCv5qZa2CJHRs7K8Ib9OBiP/Itzez/AAxujcFD/wBAXb1pf6KZUI64cIwTR4cJEB1yBZDhmGG2HYB/lXPqldQOSLHCGChG0TfssvlYwdGN+y5XLdTQdEHHGGb+UfZO4ZzauR5hPdBxzA2iKCCJtfTa3kCt1KAUGkRjXQH2V7lp2AW4geaUEGjuQAr3Q6LbQ5BKPJBq7oX9I90EIvmtpPomx0CDUY2jTRO7A1pbNynPWgg192L0GqojAWelK2KQYBgrQUgaNFlomldQghAvVK01ApNr2S/9lAoAIB0IUvVL5BArTUqgAJfqlHn90FDQAoRprqEukHlzQKVAG6KeZQXTc7oVEB9ggqbFTbbmiC+iVQUJ9Uv1QNRzVUtL01AQUb7UU33UtTU7lBTvoVddwFjpaXpzKC6+iiJe3NA00/qpR60qVNLtBroDYp5FNiaVsbkaIHoEGvknonIaILpom2gCUAmvJBQaQEcv1TlqUoIB81bHL+ClcyqNTogc6JV0KUnsgnoqeWoKtdE36ICp9E9k5IJRBAWVEKHfROWvNBQOZT7J7JyQPXRWtd012OiILfQpdGyp7q5UD0VG26AHakrVABA3S0r7KjTQIJenVZaehUSqGqBoqNBam2xVu+aC7qJat+SCA+YKuUVSVqqEVKFonNEADRND5K7pzQRXdNL8kO2yCVyKaeaK+yqJSe6vJTmopR6oBol9EJIVROeqVzVvmoVAIQbJVodNyihT7+inumtogfRL80pT1QXTmpflonoogt/9gofJNdfNLQNNFNOiunI0sSQTugvqljoh0Cl6ILeqbnopdKfyQVNlOSfxtAO2gT1GyE8tlP1QVFD5IEDXfZS+ZRDpsgt3tt5qc1iVdKQW+qX1+6xuhaUXb7oMr1qimtbqUVEGRIHVSzyFoKNKnyQSyfL0WRICxPqpfJBleieqmql+6C6pZI1Sz91OSDL2UJI5Uodt1QQOiCijzr1SiOahJCgd5ILfK0vZSydaQ7jzQU6pZUOgS/NBfZL1UBPVN0FU1U1tXbVBgK6q3osbVBCC3RpAfRTTYFNeSDKx0SwTosdUukGXssh9lhZO2iv3QZWNuaAj/ssQefNXcIMrAOhS+uqxWQqtEFvRDrqsQa3KoOvVBRvurahPkiC31S75aKWCOqu2yCpdJem6loMqtLU5dE2HVBkTrqU3Oil1om/kgzzUd/spfmVAfNAbKKp3V35rHyBQa/6ojIbIoTqiDI1soNlPXVN/JFZWl6qXSXfJBkl9FLFpeiC3Slp0TMEFFJtupm6KXrzQZWpqpdJfNEZFRS/JL6ILe+qWRupdHVW0UtROaWgt+alqWl89ERU9FL1UsBBQdUKhPol+aC2pdlL5KX0KCn1Us1val+aWQgtnZTnqpfmhOiC6A6BRLUs+yDInomlarHNSua9OSB6C0shNuShd5oFjmhN9FKQHVBdxyCgvyQm/JT3QU7qAiylqEEhA3KG7QE0pY57IKaKeql/ZOSoXzQHyU1KctkGXNSzdBEUA3fRDZPRQJrzQX9Fd+ax91RXXVBfQqXfql9FOW6CkjZLsqA6eSaVugy5qKWhNbFBkl0FjfNLKCpfNL6KHyQZXe6ibKX0KC3W6a8lPumgNUguZLtYgi1T06oMFRuomZBVdfJY3eyeZQXmr7rEHRDvugz2TNr5LHYUmiDKwl+Sl2hKCklUEqaFEFBAV9CpfJEGRtN1iT1VB10QXbmr7rEnSlQgvJUGuixvoloMrBVBCxB5hU6oMr6FS1AU90GQNj+aWLUrqpQvdBnzS+drHml9UGXur6rDRUHzQW1QsbQFBnahKxB81eaC2raxvqmlorK9eqKXoprzCIy05JssbS0GXJFjaA+aDKwlqWpaDJQqWogytL13WPLdCeSDK1LtQlLQXklqEqeqDIbbWoN1jm80tBlp0U5bICsbKDKtN1NlAUJ01QPdW+qxs9Vb03QWueyhsqElLQX1QdFLIUtBlfJTc6pv0Q0OaBrSbFS/NY2gzJoqWpeiWOiCpfQrE6hLQW1LpS+qlgIMrSqWN9Vb0tBbooSsQg9FRRtqqKKxukulBlspaAogqKXSXogXXND5LEUskAJspsqapA5aIpabhBRZRS+Sct0C1b0UvVLQXbzTRTRLQW0UT1QVTfVLCWgxGp1Ch9EB13U3QZXyRY2srQOauix1tPVBkSEFLEKlBbpVT1VtBQlarGzaqC3qrssbV33QUFULHZWwgut6KrFS0GWmZXmsbVvRBlaarG1Sa2QW9FQbCxtL6IMrRY3QVzaILrVK2sR5paDK+qoKx23UBQZeiapmUslBkEtY3SWgzu1LWKX5oM780s81jaILYtXZY2l6IMrsJosc2lKEoKDat6qKc0GVi0srAmyraDK091haEhBmpfOlM2ilmkGShI5WpsllBRVJmWKXogy80vVY35peiC3StrAlLQUHqixs9VeSCk6KEoseaDJPspqBuogyUUugiDIGimixBQnkgtoseSFBT5IFiTyQFBkR5qacliCByS1Rka56JYpYWqPRQZXqoT5qXqllBbCihUuig2Xr5KbKXe6l6IMlNOaBOSCg16JdFS0O2qCl1oSsbVzUgX91bNUpz1RBfZKCxVzIBIVCx5pogysJYGixKHXZBlaloCoSgtpzUvRDQ6IMFfdT2TkgK8tFPVNQbQZX1VtY63qiDK9VFBavNBbKApp1RBkpqor7oL6JfVS6S9UGXqreixKmwQZ+qctFj90BQZXatrH2S0GV0mYVqsbSwgyDtFbWF0qgyvVL0WKBBlatrC0DuSDO7S1jaXZQZWNktY6BUlBbQlTyUukGd6qFS9ECCgooloMrRY2Eut0GV8lL1Uu0ukFKa7FS9EsoLYpLWKWgy9FPUoTopaCk0lmljapNILdpvzWJOiWgtpy0KnJLQXWlNVL0UvRBkSixQlBkpm/RRSwOSDLlul0sbtLs7KjIlOSxSwNlBlaix1tW0AbeavLdS9FL6oLmVtY2iBaBQ77q2qF0UvnanJERLNq2iloKT0QbIsbQZac0U0U2KKysWmZT0S9EGRNjdQm1idt0tQZ5uiixCbIKdEuwpd81eSoyJUHVTMpdKDK+SLGwqCgpKA+anmlVqgu/NB5lY7oEGVhFFLQXnuroNVjeqE6IMduaWSFLKmakGSt+axtVBkSaS/NYC0vVBmCqsBRVu0GSXqsbT3QZAq3qsFUGVoCsbRBmDqhdqsUQZ2lrCzSA6IM7S1jaWgyvToixtL0QZaK2sQUtBleqtrC96VtBlySwsQUvogtqrG0QZJaxtLtBlavJYWmZBkrZAWOZS0GdpaxtL5oMilrGyloMlLUzaITZ1QX3VtY2paDPMpeixBSwgyBS1jYUtBnm5KWsbo7ITogySx0WN0EtBlY80sLC1L10QbLrmoVjY5pfRBdhRS9FjmvdUnVBbS1ilhUZKWsbQm9URlaWsQeqEorK1BdqGq3TMoMrUHmpeiXSCk6pZ6KXopqqig6q5isOSo9UVkSb2UJtQlLQVNeqxtAURkdlOSgJS1FW9Uu97UtBoNSqLaaKXYUvooMkvRYkpmFKjIFLNrG9EtQZJdrHMmZUZXScliT1S1BlyTkscyWgz91FjaloMrpXUrG0soMroFFjaIMrHNS1iSpeqC31UsLG1BdoNgNJdlYXqqDqgyvzTdYkpmQZhLWNpaDK1VgCFlfRBUWNq3ogtq31WFq5ggyvolrG1bQXNSvNY35peqDMkKXoscyBxQZBW1jaWgzvqlrC0tBnal6LE+qBBnfRLWFq2gyS1jaIMrCZliSloMrtLWBN80tBsvRS1iCraCk9EtY5ktBlmVu1rJVtBnopaxzJaDK0WNhEGR1QFYk6KWgytL00WObVMxQZXaWLWN60hKDIlPXRY2loMr6KeaLEnzQZWlrFLpBQfNW1jYUJVGV+aArG0tBlyRY3poigt2m6l9FCUGSl6KKFVGVq2FjeilqKzLlM1DRY2hVRbtBoVAUHogpcnJTRQmlBlohOqwBtVUW0zLGyFUGV6KX1WI03TMUVkClrG/ZSyVBnfVKtYpfREZKBY2lqjMHVM2iwzJfRFZE2l0sbIVvRBd1eSwvVUlQVAsQbVDkGRRYXroraCg6pagUtBknoscymbVB//2Q==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AJ12\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AJ4\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# 随机取出三张图片\n",
    "for n in range(3):\n",
    "    image_index = random.choice(range(len(all_image_path)))\n",
    "    display.display(display.Image(all_image_path[image_index]))\n",
    "    print(index_to_label[all_image_label[image_index]])\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 预处理函数，channel3表示彩色图片\n",
    "def load_preprosess(path):\n",
    "    img_raw = tf.io.read_file(path)\n",
    "    img_tensor = tf.image.decode_jpeg(img_raw, channels=3)\n",
    "    img_tensor = tf.image.resize(img_tensor, [256, 256])\n",
    "    img_tensor = tf.cast(img_tensor, tf.float32)\n",
    "    img = img_tensor/255\n",
    "    return img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_ds = tf.data.Dataset.from_tensor_slices(all_image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_dataset = path_ds.map(load_preprosess)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 标签不需要经过上述预处理\n",
    "label_dataset = tf.data.Dataset.from_tensor_slices(all_image_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<MapDataset shapes: (256, 256, 3), types: tf.float32>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将图片和标签打包成数据集\n",
    "dataset = tf.data.Dataset.zip((image_dataset, label_dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 分割训练集和测试集\n",
    "train_count = int(image_count*0.9)\n",
    "test_count = image_count - train_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = dataset.skip(test_count)\n",
    "test_dataset = dataset.take(test_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = train_dataset.shuffle(train_count).batch(batch_size)\n",
    "test_dataset = test_dataset.batch(batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
